The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10–30) and control (20–60) samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.
Hip dysplasia is a common inherited trait of dogs that results in secondary osteoarthritis. In this article the methods used to uncover the mutations contributing to this condition are reviewed, beginning with hip phenotyping. Coarse, genome-wide, microsatellite-based screens of pedigrees of greyhounds and dysplastic Labrador retrievers were used to identify linked quantitative trait loci (QTL). Fine-mapping across two chromosomes (CFA11 and 29) was employed using single nucleotide polymorphism (SNP) genotyping. Power analyses and preferential selection of dogs for ongoing SNP-based genotyping is described with the aim of refining the QTL intervals to 1–2 megabases on these and several additional chromosomes prior to candidate gene screening. The review considers how a mutation or a genetic marker such as a SNP or haplotype of SNPs might be combined with pedigree and phenotype information to create a ‘breeding value’ that could improve the accuracy of predicting a dog’s hip conformation.
Canine hip dysplasia; Genome wide screen; Microsatellites; Single nucleotide polymorphisms (SNP); Breeding values
The domestic dog exhibits greater diversity in body size than any other terrestrial vertebrate. We used a strategy that exploits the breed structure of dogs to investigate the genetic basis of size. First, through a genome-wide scan, we identified a major quantitative trait locus (QTL) on chromosome 15 influencing size variation within a single breed. Second, we examined genetic variation in the 15-megabase interval surrounding the QTL in small and giant breeds and found marked evidence for a selective sweep spanning a single gene (IGF1), encoding insulin-like growth factor 1. A single IGF1 single-nucleotide polymorphism haplotype is common to all small breeds and nearly absent from giant breeds, suggesting that the same causal sequence variant is a major contributor to body size in all small dogs.
Selective breeding offers several important advantages over using inbred strain panels in detecting genetically correlated traits to the selection phenotype. The purpose of the current study was to selectively breed for prepulse inhibition (PPI) of the acoustic startle response (ASR), to pharmacologically and behaviorally characterize the selected lines and to use the lines for quantitative trait loci (QTL) mapping. Starting with heterogeneous stock mice formed by crossing the C57BL/6J, DBA/2J, BALB/cJ and LP/J inbred strains and using a short term selective breeding strategy, animals were selected for High and Low PPI. The selection phenotype was the 80 dB prepulse tone (15 dB above the background noise). After five generations of selection, the High and Low lines differed significantly (78.1±3.1 vs. 45.2±3.9 [percent inhibition], p<0.00001). The effects of haloperidol and MK-801 on PPI were not different between the High and Low lines. However, at the highest dose tested (10 mg/kg), the High line was more sensitive than the Low line to the disruptive PPI effects of methamphetamine. The lines did not differ in terms of basal activity or methamphetamine-induced changes in locomotor activity. The High and Low lines were genotyped using a panel of 768 SNPs. Significant QTLs (LOD > 10) were detected on chromosomes 11 and 16 that appeared similar to those detected previously (Hitzemann et al. 2001; Petryshen et al. 2005). Overall, the current study illustrates that the heritability of PPI is sufficient for short term selective breeding and that the lines which are developed can be used to characterize the factors associated with the regulation of PPI.
prepulse inhibition; mice; genetics; selection; quantitative trait loci
There are around 400 internationally recognized dog breeds in the world today, with a remarkable diversity in size, shape, color and behavior. Breeds are considered to be uniform groups with similar physical characteristics, shaped by selection rooted in human preferences. This has led to a large genetic difference between breeds and a large extent of linkage disequilibrium within breeds. These characteristics are important for association mapping of candidate genes for diseases and therefore make dogs ideal models for gene mapping of human disorders. However, genetic uniformity within breeds may not always be the case. We studied patterns of genetic diversity within 164 poodles and compared it to 133 dogs from eight other breeds.
Our analyses revealed strong population structure within poodles, with differences among some poodle groups as pronounced as those among other well-recognized breeds. Pedigree analysis going three generations back in time confirmed that subgroups within poodles result from assortative mating imposed by breed standards as well as breeder preferences. Matings have not taken place at random or within traditionally identified size classes in poodles. Instead, a novel set of five poodle groups was identified, defined by combinations of size and color, which is not officially recognized by the kennel clubs. Patterns of genetic diversity in other breeds suggest that assortative mating leading to fragmentation may be a common feature within many dog breeds.
The genetic structure observed in poodles is the result of local mating patterns, implying that breed fragmentation may be different in different countries. Such pronounced structuring within dog breeds can increase the power of association mapping studies, but also represents a serious problem if ignored.
In dog breeding, individuals are selected on the basis of morphology, behaviour, working or show purposes, as well as geographic population structure. The same processes which have historically created dog breeds are still ongoing, and create further subdivision within current dog breeds.
Over the past 15 years advances in the porcine genetic linkage map and discovery of useful candidate genes have led to valuable gene and trait information being discovered. Early use of exotic breed crosses and now commercial breed crosses for quantitative trait loci (QTL) scans and candidate gene analyses have led to 110 publications which have identified 1,675 QTL. Additionally, these studies continue to identify genes associated with economically important traits such as growth rate, leanness, feed intake, meat quality, litter size, and disease resistance. A well developed QTL database called PigQTLdb is now as a valuable tool for summarizing and pinpointing in silico regions of interest to researchers. The commercial pig industry is actively incorporating these markers in marker-assisted selection along with traditional performance information to improve traits of economic performance. The long awaited sequencing efforts are also now beginning to provide sequence available for both comparative genomics and large scale single nucleotide polymorphism (SNP) association studies. While these advances are all positive, development of useful new trait families and measurement of new or underlying traits still limits future discoveries. A review of these developments is presented.
Pig; Quantitative trait Loci; QTL; genome sequence; database
A mathematical approach to optimize selection on multiple quantitative trait loci (QTL) and an estimate of residual polygenic effects was applied to selection on two linked or unlinked additive QTL. Strategies to maximize total or cumulative discounted response over ten generations were compared to standard QTL selection on the sum of breeding values for the QTL and an estimated breeding value for polygenes, and to phenotypic selection. Optimal selection resulted in greater response to selection than standard QTL or phenotypic selection. Tight linkage between the QTL (recombination rate 0.05) resulted in a slightly lower response for standard QTL and phenotypic selection but in a greater response for optimal selection. Optimal selection capitalized on linkage by emphasizing selection on favorable haplotypes. When the objective was to maximize total response after ten generations and QTL were unlinked, optimal selection increased QTL frequencies to fixation in a near linear manner. When starting frequencies were equal for the two QTL, equal emphasis was given to each QTL, regardless of the difference in effects of the QTL and regardless of the linkage, but the emphasis given to each of the two QTL was not additive. These results demonstrate the ability of optimal selection to capitalize on information on the complex genetic basis of quantitative traits that is forthcoming.
selection; marker-assisted selection; quantitative trait loci; optimization
Since the beginnings of domestication, the craniofacial architecture of the domestic dog has morphed and radiated to human whims. By beginning to define the genetic underpinnings of breed skull shapes, we can elucidate mechanisms of morphological diversification while presenting a framework for understanding human cephalic disorders. Using intrabreed association mapping with museum specimen measurements, we show that skull shape is regulated by at least five quantitative trait loci (QTLs). Our detailed analysis using whole-genome sequencing uncovers a missense mutation in BMP3. Validation studies in zebrafish show that Bmp3 function in cranial development is ancient. Our study reveals the causal variant for a canine QTL contributing to a major morphologic trait.
As a result of selective breeding practices, modern dogs display a multitude of head shapes. Breeds such as the Pug and Bulldog popularize one of these morphologies, termed “brachycephaly.” A short, upward-pointing snout, a massive and rounded head, and an underbite typify brachycephalic breeds. Here, we have coupled the phenotypes collected from museum skulls with the genotypes collected from dogs and identified five regions of the dog genome that are associated with canine brachycephaly. Fine mapping at one of these regions revealed a causal mutation in the gene BMP3. Bmp3's role in regulating cranial development is evolutionarily ancient, as zebrafish require its function to generate a normal craniofacial morphology. Our data begin to expose the genetic mechanisms unknowingly employed by breeders to create and diversify the cranial shape of dogs.
The domestic dog (Canis familiaris) segregates more naturally-occurring diseases and phenotypic variation than any other species and has become established as an unparalled model with which to study the genetics of inherited traits. We used a genome-wide association study (GWAS) and targeted resequencing of DNA from just five dogs to simultaneously map and identify mutations for two distinct inherited disorders that both affect a single breed, the Cavalier King Charles Spaniel. We investigated episodic falling (EF), a paroxysmal exertion-induced dyskinesia, alongside the phenotypically distinct condition congenital keratoconjunctivitis sicca and ichthyosiform dermatosis (CKCSID), commonly known as dry eye curly coat syndrome. EF is characterised by episodes of exercise-induced muscular hypertonicity and abnormal posturing, usually occurring after exercise or periods of excitement. CKCSID is a congenital disorder that manifests as a rough coat present at birth, with keratoconjunctivitis sicca apparent on eyelid opening at 10–14 days, followed by hyperkeratinisation of footpads and distortion of nails that develops over the next few months. We undertook a GWAS with 31 EF cases, 23 CKCSID cases, and a common set of 38 controls and identified statistically associated signals for EF and CKCSID on chromosome 7 (Praw 1.9×10−14; Pgenome = 1.0×10−5) and chromosome 13 (Praw 1.2×10−17; Pgenome = 1.0×10−5), respectively. We resequenced both the EF and CKCSID disease-associated regions in just five dogs and identified a 15,724 bp deletion spanning three exons of BCAN associated with EF and a single base-pair exonic deletion in FAM83H associated with CKCSID. Neither BCAN or FAM83H have been associated with equivalent disease phenotypes in any other species, thus demonstrating the ability to use the domestic dog to study the genetic basis of more than one disease simultaneously in a single breed and to identify multiple novel candidate genes in parallel.
The main goal in animal breeding is to select individuals that have high breeding values for traits of interest as parents to produce the next generation and to do so as quickly as possible. To date, most programs rely on statistical analysis of large data bases with phenotypes on breeding populations by linear mixed model methodology to estimate breeding values on selection candidates. However, there is a long history of research on the use of genetic markers to identify quantitative trait loci and their use in marker-assisted selection but with limited implementation in practical breeding programs. The advent of high-density SNP genotyping, combined with novel statistical methods for the use of this data to estimate breeding values, has resulted in the recent extensive application of genomic or whole-genome selection in dairy cattle and research to implement genomic selection in other livestock species is underway. The high-density SNP data also provides opportunities to detect QTL and to encover the genetic architecture of quantitative traits, in terms of the distribution of the size of genetic effects that contribute to trait differences in a population. Results show that this genetic architecture differs between traits but that for most traits, over 50% of the genetic variation resides in genomic regions with small effects that are of the order of magnitude that is expected under a highly polygenic model of inheritance.
Animal breeding; quantitative genetics; whole genome association studies; genomic selection.
Quantitative trait loci (QTL) studies provide insight into the complexity of drought tolerance mechanisms. Molecular markers used in these studies also allow for marker-assisted selection (MAS) in breeding programs, enabling transfer of genetic factors between breeding lines without complete knowledge of their exact nature. However, potential for recombination between markers and target genes limit the utility of MAS-based strategies. Candidate gene mapping offers an alternative solution to identify trait determinants underlying QTL of interest. Here, we used restriction site polymorphisms to investigate co-location of candidate genes with QTL for seedling drought stress-induced premature senescence identified previously in cowpea. Genomic DNA isolated from 113 F2:8 RILs of drought-tolerant IT93K503-1 and drought susceptible CB46 genotypes was digested with combinations of EcoR1 and HpaII, Mse1, or Msp1 restriction enzymes and amplified with primers designed from 13 drought-responsive cDNAs. JoinMap 3.0 and MapQTL 4.0 software were used to incorporate polymorphic markers onto the AFLP map and to analyze their association with the drought response QTL. Seven markers co-located with peaks of previously identified QTL. Isolation, sequencing, and blast analysis of these markers confirmed their significant homology with drought or other abiotic stress-induced expressed sequence tags (EST) from cowpea and other plant systems. Further, homology with coding sequences for a multidrug resistance protein 3 and a photosystem I assembly protein ycf3 was revealed in two of these candidates. These results provide a platform for the identification and characterization of genetic trait determinants underlying seedling drought tolerance in cowpea.
Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 × ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2–3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48–33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3–15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54–44.72% PVE) and 63 (7.11–21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7–8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2–9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut.
Electronic supplementary material
The online version of this article (doi:10.1007/s00122-010-1517-0) contains supplementary material, which is available to authorized users.
Peanut; Drought tolerance; Genetic map; Molecular markers; Main-effect QTLs; Epistatic QTLs; Molecular breeding
The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.
There are hundreds of dog breeds that exhibit massive differences in appearance and behavior sculpted by tightly controlled selective breeding. This large-scale natural experiment has provided an ideal resource that geneticists can use to search for genetic variants that control these differences. With this goal, we developed a high-density array that surveys variable sites at more than 170,000 positions in the dog genome and used it to analyze genetic variation in 46 breeds. We identify 44 chromosomal regions that are extremely variable between breeds and are likely to control many of the traits that vary between them, including curly tails and sociality. Many other regions also bear the signature of strong artificial selection. We characterize one such region, known to associate with body size and ear type, in detail using “next-generation” sequencing technology to identify candidate mutations that may control these traits. Our results suggest that artificial selection has targeted genes involved in development and metabolism and that it may have increased the incidence of disease in dog breeds. Knowledge of these regions will be of great importance for uncovering the genetic basis of variation between dog breeds and for finding mutations that cause disease.
The genetic dissection of complex traits plays a crucial role in crop breeding. However, genetic analysis and crop breeding have heretofore been performed separately. In this study, we designed a new approach that integrates epistatic association analysis in crop cultivars with breeding by design. First, we proposed an epistatic association mapping (EAM) approach in homozygous crop cultivars. The phenotypic values of complex traits, along with molecular marker information, were used to perform EAM. In our EAM, all the main-effect quantitative trait loci (QTLs), environmental effects, QTL-by-environment interactions and QTL-by-QTL interactions were included in a full model and estimated by empirical Bayes approach. A series of Monte Carlo simulations was performed to confirm the reliability of the new method. Next, the information from all detected QTLs was used to mine novel alleles for each locus and to design elite cross combination. Finally, the new approach was adopted to dissect the genetic basis of seed length in 215 soybean cultivars obtained, by stratified random sampling, from 6 geographic ecotypes in China. As a result, 19 main-effect QTLs and 3 epistatic QTLs were identified, more than 10 novel alleles were mined and 3 elite parental combinations, such as Daqingdou and Zhengzhou790034, were predicted.
The largest genetic study to date of morphology in domestic dogs identifies genes
controlling nearly 100 morphological traits and identifies important trends in
phenotypic variation within this species.
Domestic dogs exhibit tremendous phenotypic diversity, including a greater
variation in body size than any other terrestrial mammal. Here, we generate a
high density map of canine genetic variation by genotyping 915 dogs from 80
domestic dog breeds, 83 wild canids, and 10 outbred African shelter dogs across
60,968 single-nucleotide polymorphisms (SNPs). Coupling this genomic resource
with external measurements from breed standards and individuals as well as
skeletal measurements from museum specimens, we identify 51 regions of the dog
genome associated with phenotypic variation among breeds in 57 traits. The
complex traits include average breed body size and external body dimensions and
cranial, dental, and long bone shape and size with and without allometric
scaling. In contrast to the results from association mapping of quantitative
traits in humans and domesticated plants, we find that across dog breeds, a
small number of quantitative trait loci (≤3) explain the majority of
phenotypic variation for most of the traits we studied. In addition, many
genomic regions show signatures of recent selection, with most of the highly
differentiated regions being associated with breed-defining traits such as body
size, coat characteristics, and ear floppiness. Our results demonstrate the
efficacy of mapping multiple traits in the domestic dog using a database of
genotyped individuals and highlight the important role human-directed selection
has played in altering the genetic architecture of key traits in this important
Dogs offer a unique system for the study of genes controlling morphology. DNA
from 915 dogs from 80 domestic breeds, as well as a set of feral dogs, was
tested at over 60,000 points of variation and the dataset analyzed using novel
methods to find loci regulating body size, head shape, leg length, ear position,
and a host of other traits. Because each dog breed has undergone strong
selection by breeders to have a particular appearance, there is a strong
footprint of selection in regions of the genome that are important for
controlling traits that define each breed. These analyses identified new regions
of the genome, or loci, that are important in controlling body size and shape.
Our results, which feature the largest number of domestic dogs studied at such a
high level of genetic detail, demonstrate the power of the dog as a model for
finding genes that control the body plan of mammals. Further, we show that the
remarkable diversity of form in the dog, in contrast to some other species
studied to date, appears to have a simple genetic basis dominated by genes of
Analysis of the genetic variation of an endangered population is an important component for the success of conservation. Animals from two local Romanian pig breeds, the Mangalitsa and Bazna, were analysed for variation at a number of genetic loci using PCR-based DNA tests. Polymorphism was assessed at loci which 1) are known to cause phenotypic variation, 2) are potentially involved in trait differences or 3) are putative candidate genes. The traits considered are disease resistance, growth, coat colour, meat quality and prolificacy. Even though the populations are small and the markers are limited to specific genes, we found significant differences in five of the ten characterised loci. In some cases the observed allele frequencies were interesting in relation to gene function and the phenotype of the breed. These breeds are part of a conservation programme in Romania and marker information may be useful in preserving a representative gene pool in the populations. The use of polymorphisms in type 1 (gene) markers may be a useful complement to analysis based on anonymous markers.
pig; genetic diversity; local breeds
The process of aging can be described as a progressive decline in an organism's function that invariably results in death. This decline results from the activities of intrinsic genetic factors within an organism. The relative contributions of the biological and environmental components to senescence are hard to measure, however different strategies have been devised in Drosophila melanogaster to isolate and identify genetic influences on aging. These strategies include selective breeding, quantitative trait loci (QTL) mapping and single gene mutant analysis. Selective breeding effectively demonstrated a genetic, heritable component to aging while QTL mapping located regions within the Drosophila genome carrying loci that influence the aging process. Within the past decade, single gene mutant analysis has facilitated the identification of specific genes whose activities play a determinative role in Drosophila aging. This review will focus on the application of selective breeding, QTL mapping and single gene mutant analysis used in Drosophila to study aging as well as the results obtained through these strategies to date.
biomarkers; enhancer-trap; functional senescence; gene expression; longevity; microarray; QTL mapping; selective breeding; stress; UAS/GAL4
The number of vertebrae in pigs varies and is associated with body size. Wild boars have 19 vertebrae, but European commercial breeds for pork production have 20 to 23 vertebrae. We previously identified two quantitative trait loci (QTLs) for number of vertebrae on Sus scrofa chromosomes (SSC) 1 and 7, and reported that an orphan nuclear receptor, NR6A1, was located at the QTL on SSC1. At the NR6A1 locus, wild boars and Asian local breed pigs had the wild-type allele and European commercial-breed pigs had an allele associated with increased numbers of vertebrae (number-increase allele).
Here, we performed a map-based study to define the other QTL, on SSC7, for which we detected genetic diversity in European commercial breeds. Haplotype analysis with microsatellite markers revealed a 41-kb conserved region within all the number-increase alleles in the present study. We also developed single nucleotide polymorphisms (SNPs) in the 450-kb region around the QTL and used them for a linkage disequilibrium analysis and an association study in 199 independent animals. Three haplotype blocks were detected, and SNPs in the 41-kb region presented the highest associations with the number of vertebrae. This region encodes an uncharacterized hypothetical protein that is not a member of any other known gene family. Orthologs appear to exist not only in mammals but also birds and fish. This gene, which we have named vertnin (VRTN) is a candidate for the gene associated with variation in vertebral number. In pigs, the number-increase allele was expressed more abundantly than the wild-type allele in embryos. Among candidate polymorphisms, there is an insertion of a SINE element (PRE1) into the intron of the Q allele as well as the SNPs in the promoter region.
Genetic diversity of VRTN is the suspected cause of the heterogeneity of the number of vertebrae in commercial-breed pigs, so the polymorphism information should be directly useful for assessing the genetic ability of individual animals. The number-increase allele of swine VRTN was suggested to add an additional thoracic segment to the animal. Functional analysis of VRTN may provide novel findings in the areas of developmental biology.
One of the main limitations of many livestock breeding programs is that selection is in pure breeds housed in high-health environments but the aim is to improve crossbred performance under field conditions. Genomic selection (GS) using high-density genotyping could be used to address this. However in crossbred populations, 1) effects of SNPs may be breed specific, and 2) linkage disequilibrium may not be restricted to markers that are tightly linked to the QTL. In this study we apply GS to select for commercial crossbred performance and compare a model with breed-specific effects of SNP alleles (BSAM) to a model where SNP effects are assumed the same across breeds (ASGM). The impact of breed relatedness (generations since separation), size of the population used for training, and marker density were evaluated. Trait phenotype was controlled by 30 QTL and had a heritability of 0.30 for crossbred individuals. A Bayesian method (Bayes-B) was used to estimate the SNP effects in the crossbred training population and the accuracy of resulting GS breeding values for commercial crossbred performance was validated in the purebred population.
Results demonstrate that crossbred data can be used to evaluate purebreds for commercial crossbred performance. Accuracies based on crossbred data were generally not much lower than accuracies based on pure breed data and almost identical when the breeds crossed were closely related breeds. The accuracy of both models (ASGM and BSAM) increased with marker density and size of the training data. Accuracies of both models also tended to decrease with increasing distance between breeds. However the effect of marker density, training data size and distance between breeds differed between the two models. BSAM only performed better than AGSM when the number of markers was small (500), the number of records used for training was large (4000), and when breeds were distantly related or unrelated.
In conclusion, GS can be conducted in crossbred population and models that fit breed-specific effects of SNP alleles may not be necessary, especially with high marker density. This opens great opportunities for genetic improvement of purebreds for performance of their crossbred descendents in the field, without the need to track pedigrees through the system.
Unraveling the genetic background of economic traits is a major goal in modern animal genetics and breeding. Both candidate gene analysis and QTL mapping have previously been used for identifying genes and chromosome regions related to studied traits. However, most of these studies may be limited in their ability to fully consider how multiple genetic factors may influence a particular phenotype of interest. If possible, taking advantage of the combined effect of multiple genetic factors is expected to be more powerful than analyzing single sites, as the joint action of multiple loci within a gene or across multiple genes acting in the same gene set will likely have a greater influence on phenotypic variation. Thus, we proposed a pipeline of gene set analysis that utilized information from multiple loci to improve statistical power. We assessed the performance of this approach by both simulated and a real IGF1-FoxO pathway data set. The results showed that our new method can identify the association between genetic variation and phenotypic variation with higher statistical power and unravel the mechanisms of complex traits in a point of gene set. Additionally, the proposed pipeline is flexible to be extended to model complex genetic structures that include the interactions between different gene sets and between gene sets and environments.
The tendency for male-larger sexual size dimorphism (SSD) to scale with body size – a pattern termed Rensch's rule – has been empirically supported in many animal lineages. Nevertheless, its theoretical elucidation is a subject of debate. Here, we exploited the extreme morphological variability of domestic dog (Canis familiaris) to gain insights into evolutionary causes of this rule.
We studied SSD and its allometry among 74 breeds ranging in height from less than 19 cm in Chihuahua to about 84 cm in Irish wolfhound. In total, the dataset included 6,221 individuals. We demonstrate that most dog breeds are male-larger, and SSD in large breeds is comparable to SSD of their wolf ancestor. Among breeds, SSD becomes smaller with decreasing body size. The smallest breeds are nearly monomorphic.
SSD among dog breeds follows the pattern consistent with Rensch's rule. The variability of body size and corresponding changes in SSD among breeds of a domestic animal shaped by artificial selection can help to better understand processes leading to emergence of Rensch's rule.
Polymorphism in genes of regulating enzymes, transporters and receptors of the neurotransmitters of the central nervous system have been associated with altered behaviour, and single nucleotide polymorphisms (SNPs) represent the most frequent type of genetic variation. The serotonin and dopamine signalling systems have a central influence on different behavioural phenotypes, both of invertebrates and vertebrates, and this study was undertaken in order to explore genetic variation that may be associated with variation in behaviour.
Single nucleotide polymorphisms in canine genes related to behaviour were identified by individually sequencing eight dogs (Canis familiaris) of different breeds. Eighteen genes from the dopamine and the serotonin systems were screened, revealing 34 SNPs distributed in 14 of the 18 selected genes. A total of 24,895 bp coding sequence was sequenced yielding an average frequency of one SNP per 732 bp (1/732). A total of 11 non-synonymous SNPs (nsSNPs), which may be involved in alteration of protein function, were detected. Of these 11 nsSNPs, six resulted in a substitution of amino acid residue with concomitant change in structural parameters.
We have identified a number of coding SNPs in behaviour-related genes, several of which change the amino acids of the proteins. Some of the canine SNPs exist in codons that are evolutionary conserved between five compared species, and predictions indicate that they may have a functional effect on the protein. The reported coding SNP frequency of the studied genes falls within the range of SNP frequencies reported earlier in the dog and other mammalian species. Novel SNPs are presented and the results show a significant genetic variation in expressed sequences in this group of genes. The results can contribute to an improved understanding of the genetics of behaviour.
Cotton fiber is an ideal model to study cell elongation and cell wall construction in plants. During fiber development, some genes and proteins have been reported to be specifically or preferentially expressed. Mapping of them will reveal the genomic distribution of these genes, and will facilitate selection in cotton breeding. Based on previous reports, we designed 331 gene primers and 164 protein primers, and used single-strand conformation polymorphism (SSCP) to map and integrate them into our interspecific BC1 linkage map. This resulted in the mapping of 57 loci representing 51 genes or proteins on 22 chromosomes. For those three markers which were tightly linked with quantitative trait loci (QTLs), the QTL functions obtained in this study and gene functions reported in previous reports were consistent. Reverse transcription-polymerase chain reaction (RT-PCR) analysis of 52 polymorphic functional primers showed that 21 gene primers and 17 protein primers had differential expression between Emian22 (Gossypium hirsutum) and 3–79 (G. barbadense). Both RT-PCR and quantitative real-time PCR (qRT-PCR) analyses of the three markers tightly linked with QTLs were consistent with QTL analysis and field experiments. Gene Ontology (GO) categorization revealed that almost all 51 mapped genes belonged to multiple categories that contribute to fiber development, indicating that fiber development is a complex process regulated by various genes. These 51 genes were all specifically or preferentially expressed during fiber cell elongation and secondary wall biosynthesis. Therefore, these functional gene-related markers would be beneficial for the genetic improvement of cotton fiber length and strength.
The present research examined developmental and gender differences in the relative accessibility of different gender stereotype domains. A 1988 Northeastern US sample of 256 children ages 3 to 10 years old provided open-ended descriptions of girls and boys. Responses were coded by domain to examine differences by grade, gender of participant, and gender of target. Analyses revealed that girls and older children provided a higher proportion of stereotypes, and that appearance stereotypes were particularly prevalent in descriptions of girls and activity/trait stereotypes were more prevalent in descriptions of boys. Results are discussed in terms of implications for research on the stereotype knowledge–behavior link and the need for more attention to the role of appearance stereotypes in the gender stereotype literature.
Stereotype domains; Gender stereotypes; Stereotype accessibility; Gender differences
Studies using inbred strains of mice have been invaluable for identifying alleles that adversely affect hearing. However, the efficacy of those studies is limited by the phenotypes that these strains express and the alleles that they segregate. Here, by selectively breeding phenotypically and genetically heterogeneous NIH Swiss mice, we generated two lines—the all-frequency hearing loss (AFHL) line and the high-frequency hearing loss (HFHL) line—with differential hearing loss. The AFHL line exhibited characteristics typical of severe, early-onset, sensorineural hearing impairment. In contrast, the HFHL line expressed a novel early-onset, mildly progressive, and frequency-specific sensorineural hearing loss. By quantitative trait loci (QTLs) analyses in these two lines, we identified QTLs on chromosomes 7, 8, and 10 that significantly affected hearing function. The loci on chromosomes 7 and 8 (Hfhl1 and Hfhl2, respectively) are novel and appear to adversely affect only high frequencies (≥30 kHz). Mice homozygous for NIH Swiss alleles at either Hfhl1 or Hfhl2 have 32-kHz auditory-evoked brain stem response thresholds that are 8–14 dB SPL higher than the corresponding heterozygotes. DNA sequence analyses suggest that both the Cdh23ahl and Gipc3ahl5 variants contribute to the chromosome 10 QTL detected in the AFHL line. The frequency-specific hearing loss indicates that the Hfhl1 and Hfhl2 alleles may affect tonotopic development. In addition, dissecting the underlying complex genetics of high-frequency hearing loss may prove relevant in identifying less severe and common forms of hearing impairment in the human population.
NIH Swiss; sensorineural hearing loss; quantitative trait locus analysis