Mapping and Functional Dissection of the Rumpless Trait in Piao Chicken Identifies a Causal Loss of Function Mutation in the Novel Gene Rum.

Rumpless chickens exhibit an abnormality in their tail development. The genetics and biology of this trait has been studied for decades to illustrate a broad variation in both the types of inheritance and the severity in the developmental defects of the tail. In this study, we created a backcross pedigree by intercrossing Piao (rumpless) with Xianju (normal) to investigate the genetic mechanisms and molecular basis of the rumpless trait in Piao chicken. Through genome-wide association and linkage analyses, the candidate region was fine-mapped to 798.5 kb (chromosome 2: 86.9 to 87.7 Mb). Whole-genome sequencing analyses identified a single variant, a 4.2 kb deletion, which was completely associated with the rumpless phenotype. Explorations of the expression data identified a novel causative gene, Rum, that produced a long, intronless transcript across the deletion. The expression of Rum is embryo-specific, and it regulates the expression of MSGN1, a key factor in regulating T-box transcription factors required for mesoderm formation and differentiation. These results provide genetic and molecular experimental evidence for a novel mechanism regulating tail development in chicken and report the likely causal mutation for the tail abnormity in the Piao chicken. The novel regulatory gene, Rum, will, due to its role in fundamental embryo development, be of interest for further explorations of a potential role in tail and skeletal development also in other vertebrates.

Dynamic genetic architecture of yeast response to environmental perturbation shed light on origin of cryptic genetic variation.

Cryptic genetic variation could arise from, for example, Gene-by-Gene (G-by-G) or Gene-by-Environment (G-by-E) interactions. The underlying molecular mechanisms and how they influence allelic effects and the genetic variance of complex traits is largely unclear. Here, we empirically explored the role of environmentally influenced epistasis on the suppression and release of cryptic variation by reanalysing a dataset of 4,390 haploid yeast segregants phenotyped on 20 different media. The focus was on 130 epistatic loci, each contributing to segregant growth in at least one environment and that together explained most (69-100%) of the narrow sense heritability of growth in the individual environments. We revealed that the epistatic growth network reorganised upon environmental changes to alter the estimated marginal (additive) effects of the individual loci, how multi-locus interactions contributed to individual segregant growth and the level of expressed genetic variance in growth. The estimated additive effects varied most across environments for loci that were highly interactive network hubs in some environments but had few or no interactors in other environments, resulting in changes in total genetic variance across environments. This environmentally dependent epistasis was thus an important mechanism for the suppression and release of cryptic variation in this population. Our findings increase the understanding of the complex genetic mechanisms leading to cryptic variation in populations, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits in breeding and evolution.

A Polygenic Genetic Architecture of Flowering Time in the Worldwide Arabidopsis thaliana Population.

Here, we report an empirical study of the polygenic basis underlying the evolution of complex traits. Flowering time variation measured at 10 and 16°C in the 1,001-genomes Arabidopsis thaliana collection of natural accessions were used as a model. The polygenic architecture of flowering time was defined as the 48 loci that were significantly associated with flowering time-at 10 and/or 16°C and/or their difference-in this population. Contributions from alleles at flowering time associated loci to global and local adaptation were explored by evaluating their distribution across genetically and geographically defined subpopulations across the native range of the species. The dynamics in the genetic architecture of flowering time in response to temperature was evaluated by estimating how the effects of these loci on flowering changed with growth temperature. Overall, the genetic basis of flowering time was stable-about 2/3 of the flowering time loci had similar effects at 10°C and 16°C-but many loci were involved in gene by temperature interactions. Globally present alleles, mostly of moderate effect, contributed to the differences in flowering times between the subpopulations via subtle changes in allele frequencies. More extreme local adaptations were, on several occasions, due to regional alleles with relatively large effects, and their linkage disequilibrium-patterns suggest coevolution of functionally connected alleles within local populations. Overall, these findings provide a significant contribution to our understanding about the possible modes of global and local evolution of a complex adaptive trait in A. thaliana.

Genotyping by low-coverage whole-genome sequencing in intercross pedigrees from outbred founders: a cost-efficient approach.

BACKGROUND: Experimental intercrosses between outbred founder populations are powerful resources for mapping loci that contribute to complex traits i.e. quantitative trait loci (QTL). Here, we present an approach and its accompanying software for high-resolution reconstruction of founder mosaic genotypes in the intercross offspring from such populations using whole-genome high-coverage sequence data on founder individuals (~ 30×) and very low-coverage sequence data on intercross individuals (< 0.5×). Sets of founder-line informative markers were selected for each full-sib family and used to infer the founder mosaic genotypes of the intercross individuals. The application of this approach and the quality of the estimated genome-wide genotypes are illustrated in a large F2 pedigree between two divergently selected lines of chickens. RESULTS: We describe how we obtained whole-genome genotype data for hundreds of individuals in a cost- and time-efficient manner by using a Tn5-based library preparation protocol and an imputation algorithm that was optimized for this application. In total, 7.6 million markers segregated in this pedigree and, within each full-sib family, between 10.0 and 13.7% of these were fully informative, i.e. fixed for alternative alleles in the founders from the divergent lines, and were used for reconstruction of the offspring mosaic genotypes. The genotypes that were estimated based on the low-coverage sequence data were highly consistent (> 95% agreement) with those obtained using individual single nucleotide polymorphism (SNP) genotyping. The estimated resolution of the inferred recombination breakpoints was relatively high, with 50% of them being defined on regions shorter than 10 kb. CONCLUSIONS: A method and software for inferring founder mosaic genotypes in intercross offspring from low-coverage whole-genome sequencing in pedigrees from heterozygous founders are described. They provide high-quality, high-resolution genotypes in a time- and cost-efficient manner. The software is freely available at https://github.com/CarlborgGenomics/Stripes .

A Complex Structural Variation on Chromosome 27 Leads to the Ectopic Expression of HOXB8 and the Muffs and Beard Phenotype in Chickens.

Muffs and beard (Mb) is a phenotype in chickens where groups of elongated feathers gather from both sides of the face (muffs) and below the beak (beard). It is an autosomal, incomplete dominant phenotype encoded by the Muffs and beard (Mb) locus. Here we use genome-wide association (GWA) analysis, linkage analysis, Identity-by-Descent (IBD) mapping, array-CGH, genome re-sequencing and expression analysis to show that the Mb allele causing the Mb phenotype is a derived allele where a complex structural variation (SV) on GGA27 leads to an altered expression of the gene HOXB8. This Mb allele was shown to be completely associated with the Mb phenotype in nine other independent Mb chicken breeds. The Mb allele differs from the wild-type mb allele by three duplications, one in tandem and two that are translocated to that of the tandem repeat around 1.70 Mb on GGA27. The duplications contain total seven annotated genes and their expression was tested during distinct stages of Mb morphogenesis. A continuous high ectopic expression of HOXB8 was found in the facial skin of Mb chickens, strongly suggesting that HOXB8 directs this regional feather-development. In conclusion, our results provide an interesting example of how genomic structural rearrangements alter the regulation of genes leading to novel phenotypes. Further, it again illustrates the value of utilizing derived phenotypes in domestic animals to dissect the genetic basis of developmental traits, herein providing novel insights into the likely role of HOXB8 in feather development and differentiation.

Artificial Selection Response due to Polygenic Adaptation from a Multilocus, Multiallelic Genetic Architecture.

The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity.

Reassess the t Test: Interact with All Your Data via ANOVA.

Plant biology is rapidly entering an era where we have the ability to conduct intricate studies that investigate how a plant interacts with the entirety of its environment. This requires complex, large studies to measure how plant genotypes simultaneously interact with a diverse array of environmental stimuli. Successful interpretation of the results from these studies requires us to transition away from the traditional standard of conducting an array of pairwise t tests toward more general linear modeling structures, such as those provided by the extendable ANOVA framework. In this Perspective, we present arguments for making this transition and illustrate how it will help to avoid incorrect conclusions in factorial interaction studies (genotype × genotype, genotype × treatment, and treatment × treatment, or higher levels of interaction) that are becoming more prevalent in this new era of plant biology.

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance.

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or "missing heritability". Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

Multiple Changes of Gene Expression and Function Reveal Genomic and Phenotypic Complexity in SLE-like Disease.

The complexity of clinical manifestations commonly observed in autoimmune disorders poses a major challenge to genetic studies of such diseases. Systemic lupus erythematosus (SLE) affects humans as well as other mammals, and is characterized by the presence of antinuclear antibodies (ANA) in patients' sera and multiple disparate clinical features. Here we present evidence that particular sub-phenotypes of canine SLE-related disease, based on homogenous (ANA(H)) and speckled ANA (ANA(S)) staining pattern, and also steroid-responsive meningitis-arteritis (SRMA) are associated with different but overlapping sets of genes. In addition to association to certain MHC alleles and haplotypes, we identified 11 genes (WFDC3, HOMER2, VRK1, PTPN3, WHAMM, BANK1, AP3B2, DAPP1, LAMTOR3, DDIT4L and PPP3CA) located on five chromosomes that contain multiple risk haplotypes correlated with gene expression and disease sub-phenotypes in an intricate manner. Intriguingly, the association of BANK1 with both human and canine SLE appears to lead to similar changes in gene expression levels in both species. Our results suggest that molecular definition may help unravel the mechanisms of different clinical features common between and specific to various autoimmune disease phenotypes in dogs and humans.

Genome-wide standing variation facilitates long-term response to bidirectional selection for antibody response in chickens.

BACKGROUND: Long-term selection experiments provide a powerful approach to gain empirical insights into adaptation, allowing researchers to uncover the targets of selection and infer their contributions to the mode and tempo of adaptation. Here we implement a pooled genome re-sequencing approach to investigate the consequences of 39 generations of bidirectional selection in White Leghorn chickens on a humoral immune trait: antibody response to sheep red blood cells. RESULTS: We observed wide genome involvement in response to this selection regime. Many genomic regions were highly differentiated resulting from this experimental selection regime, an involvement of up to 20% of the chicken genome (208.8 Mb). While genetic drift has certainly contributed to this, we implement gene ontology, association analysis and population simulations to increase our confidence in candidate selective sweeps. Three strong candidate genes, MHC, SEMA5A and TGFBR2, are also presented. CONCLUSIONS: The extensive genomic changes highlight the polygenic genetic architecture of antibody response in these chicken populations, which are derived from a common founder population, demonstrating the extent of standing immunogenetic variation available at the onset of selection.

On the relationship between epistasis and genetic variance heterogeneity.

Epistasis and genetic variance heterogeneity are two non-additive genetic inheritance patterns that are often, but not always, related. Here we use theoretical examples and empirical results from earlier analyses of experimental data to illustrate the connection between the two. This includes an introduction to the relationship between epistatic gene action, statistical epistasis, and genetic variance heterogeneity, and a brief discussion about how genetic processes other than epistasis can also give rise to genetic variance heterogeneity.

Genetics of Interactive Behavior in Silver Foxes (Vulpes vulpes).

Individuals involved in a social interaction exhibit different behavioral traits that, in combination, form the individual's behavioral responses. Selectively bred strains of silver foxes (Vulpes vulpes) demonstrate markedly different behaviors in their response to humans. To identify the genetic basis of these behavioral differences we constructed a large F2 population including 537 individuals by cross-breeding tame and aggressive fox strains. 98 fox behavioral traits were recorded during social interaction with a human experimenter in a standard four-step test. Patterns of fox behaviors during the test were evaluated using principal component (PC) analysis. Genetic mapping identified eight unique significant and suggestive QTL. Mapping results for the PC phenotypes from different test steps showed little overlap suggesting that different QTL are involved in regulation of behaviors exhibited in different behavioral contexts. Many individual behavioral traits mapped to the same genomic regions as PC phenotypes. This provides additional information about specific behaviors regulated by these loci. Further, three pairs of epistatic loci were also identified for PC phenotypes suggesting more complex genetic architecture of the behavioral differences between the two strains than what has previously been observed.

Natural CMT2 variation is associated with genome-wide methylation changes and temperature seasonality.

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.

A century after Fisher: time for a new paradigm in quantitative genetics.

Quantitative genetics traces its roots back through more than a century of theory, largely formed in the absence of directly observable genotype data, and has remained essentially unchanged for decades. By contrast, molecular genetics arose from direct observations and is currently undergoing rapid changes, making the amount of available data ever greater. Thus, the two disciplines are disparate both in their origins and their current states, yet they address the same fundamental question: how does the genotype affect the phenotype? The rapidly accumulating genomic data necessitate sophisticated analysis, but many of the current tools are adaptations of methods designed during the early days of quantitative genetics. We argue here that the present analysis paradigm in quantitative genetics is at its limits in regards to unraveling complex traits and it is necessary to re-evaluate the direction that genetic research is taking for the field to realize its full potential.

cgmisc: enhanced genome-wide association analyses and visualization.

UNLABELLED: High-throughput genotyping and sequencing technologies facilitate studies of complex genetic traits and provide new research opportunities. The increasing popularity of genome-wide association studies (GWAS) leads to the discovery of new associated loci and a better understanding of the genetic architecture underlying not only diseases, but also other monogenic and complex phenotypes. Several softwares are available for performing GWAS analyses, R environment being one of them. RESULTS: We present cgmisc, an R package that enables enhanced data analysis and visualization of results from GWAS. The package contains several utilities and modules that complement and enhance the functionality of the existing software. It also provides several tools for advanced visualization of genomic data and utilizes the power of the R language to aid in preparation of publication-quality figures. Some of the package functions are specific for the domestic dog (Canis familiaris) data. AVAILABILITY AND IMPLEMENTATION: The package is operating system-independent and is available from: https://github.com/cgmisc-team/cgmisc CONTACT: marcin.kierczak@imbim.uu.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Whole-genome resequencing reveals loci under selection during chicken domestication.

Domestic animals are excellent models for genetic studies of phenotypic evolution. They have evolved genetic adaptations to a new environment, the farm, and have been subjected to strong human-driven selection leading to remarkable phenotypic changes in morphology, physiology and behaviour. Identifying the genetic changes underlying these developments provides new insight into general mechanisms by which genetic variation shapes phenotypic diversity. Here we describe the use of massively parallel sequencing to identify selective sweeps of favourable alleles and candidate mutations that have had a prominent role in the domestication of chickens (Gallus gallus domesticus) and their subsequent specialization into broiler (meat-producing) and layer (egg-producing) chickens. We have generated 44.5-fold coverage of the chicken genome using pools of genomic DNA representing eight different populations of domestic chickens as well as red jungle fowl (Gallus gallus), the major wild ancestor. We report more than 7,000,000 single nucleotide polymorphisms, almost 1,300 deletions and a number of putative selective sweeps. One of the most striking selective sweeps found in all domestic chickens occurred at the locus for thyroid stimulating hormone receptor (TSHR), which has a pivotal role in metabolic regulation and photoperiod control of reproduction in vertebrates. Several of the selective sweeps detected in broilers overlapped genes associated with growth, appetite and metabolic regulation. We found little evidence that selection for loss-of-function mutations had a prominent role in chicken domestication, but we detected two deletions in coding sequences that we suggest are functionally important. This study has direct application to animal breeding and enhances the importance of the domestic chicken as a model organism for biomedical research.

Genome-wide analysis in German shepherd dogs reveals association of a locus on CFA 27 with atopic dermatitis.

Humans and dogs are both affected by the allergic skin disease atopic dermatitis (AD), caused by an interaction between genetic and environmental factors. The German shepherd dog (GSD) is a high-risk breed for canine AD (CAD). In this study, we used a Swedish cohort of GSDs as a model for human AD. Serum IgA levels are known to be lower in GSDs compared to other breeds. We detected significantly lower IgA levels in the CAD cases compared to controls (p = 1.1 × 10(-5)) in our study population. We also detected a separation within the GSD cohort, where dogs could be grouped into two different subpopulations. Disease prevalence differed significantly between the subpopulations contributing to population stratification (λ = 1.3), which was successfully corrected for using a mixed model approach. A genome-wide association analysis of CAD was performed (n cases = 91, n controls = 88). IgA levels were included in the model, due to the high correlation between CAD and low IgA levels. In addition, we detected a correlation between IgA levels and the age at the time of sampling (corr = 0.42, p = 3.0 × 10(-9)), thus age was included in the model. A genome-wide significant association was detected on chromosome 27 (praw = 3.1 × 10(-7), pgenome = 0.03). The total associated region was defined as a ~1.5-Mb-long haplotype including eight genes. Through targeted re-sequencing and additional genotyping of a subset of identified SNPs, we defined 11 smaller haplotype blocks within the associated region. Two blocks showed the strongest association to CAD. The ~209-kb region, defined by the two blocks, harbors only the PKP2 gene, encoding Plakophilin 2 expressed in the desmosomes and important for skin structure. Our results may yield further insight into the genetics behind both canine and human AD.

Mitogenomic analysis of a 50-generation chicken pedigree reveals a rapid rate of mitochondrial evolution and evidence for paternal mtDNA inheritance.

Mitochondrial genomes represent a valuable source of data for evolutionary research, but studies of their short-term evolution have typically been limited to invertebrates, humans and laboratory organisms. Here we present a detailed study of 12 mitochondrial genomes that span a total of 385 transmissions in a well-documented 50-generation pedigree in which two lineages of chickens were selected for low and high juvenile body weight. These data allowed us to test the hypothesis of time-dependent evolutionary rates and the assumption of strict maternal mitochondrial transmission, and to investigate the role of mitochondrial mutations in determining phenotype. The identification of a non-synonymous mutation in ND4L and a synonymous mutation in CYTB, both novel mutations in Gallus, allowed us to estimate a molecular rate of 3.13 × 10(-7) mutations/site/year (95% confidence interval 3.75 × 10(-8)-1.12 × 10(-6)). This is substantially higher than avian rate estimates based upon fossil calibrations. Ascertaining which of the two novel mutations was present in an additional 49 individuals also revealed an instance of paternal inheritance of mtDNA. Lastly, an association analysis demonstrated that neither of the point mutations was strongly associated with the phenotypic differences between the two selection lines. Together, these observations reveal the highly dynamic nature of mitochondrial evolution over short time periods.

Inheritance beyond plain heritability: variance-controlling genes in Arabidopsis thaliana.

The phenotypic effect of a gene is normally described by the mean-difference between alternative genotypes. A gene may, however, also influence the phenotype by causing a difference in variance between genotypes. Here, we reanalyze a publicly available Arabidopsis thaliana dataset [1] and show that genetic variance heterogeneity appears to be as common as normal additive effects on a genomewide scale. The study also develops theory to estimate the contributions of variance differences between genotypes to the phenotypic variance, and this is used to show that individual loci can explain more than 20% of the phenotypic variance. Two well-studied systems, cellular control of molybdenum level by the ion-transporter MOT1 and flowering-time regulation by the FRI-FLC expression network, and a novel association for Leaf serration are used to illustrate the contribution of major individual loci, expression pathways, and gene-by-environment interactions to the genetic variance heterogeneity.