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A long-coated White German Shepherd Other names American White Shepherd, White Canadian Shepherd Origin Germany, Austria, and Switzerland Traits Weight Male 75–85 lb (34–39 kg) Female 60–70 lb (27–32 kg) Height Male 25 in (64 cm) Female 23 in (58 cm) Coat double coat that is straight and dense Color White, off white Litter size 5–10 Life span 12–14 years Classification / standards Herding dog ( Canis lupus familiaris) The White Shepherd emerged from white-coat lines of the dog in Canada and the United States and from European imports. The German Shepherd and the white German Shepherd are the same dog, though their coat colors vary.
The White Shepherd breed was officially recognized by the on April 14, 1999. A White Shepherd puppy, 4 months old, playing outside. In German Shepherds, the recessive gene for white coat hair was cast in the breed gene pool by the late 19th and early 20th century breeding program that developed and expanded the German Shepherd Dog breed in Germany. A white herding dog named Greif was the grandfather of, the dog acknowledged as the foundation of all contemporary German Shepherd bloodlines. Information provided in early books on the German Shepherd make mention of Greif and other white German herding dogs, with upright ears and a general body description that resembles modern German Shepherd Dogs, shown in Europe as early as 1882.
The early 20th century German Shepherd breeding program extensively line bred and inbred 'color coat' dogs that carried Greif's recessive gene for 'white coats' to refine and expand the population of early German Shepherd Dogs. White coats were made a disqualification in the German Shepherd Dog Club of Germany breed standard in 1933 after the breed club came under the control of the German Nazi party that took over all aspects of German society in February 1933 when declared a. The German breed standard remained unchanged as German breeders repopulated the breed in the years after the conclusion of WWII.
In 1959 the German Shepherd Dog Club of America (GSDCA) adopted the exclusively colored breed standard of the parent German breed club. White-coated German Shepherd Dogs were officially barred from competition in the American Kennel Club conformation ring in the United States starting in 1968. AKC-registered white German Shepherd Dogs may still compete in performance events. During 1969, white dog fanciers in the United States and Canada formed their own 'White German Shepherd' breed clubs, breeding and showing their dogs at small specialty dog shows throughout North America.
The White Shepherd Club of Canada (WSCC) has been dedicated to the promotion and preservation of the White Shepherd since 1971. Originally formed as a Chapter of the White German Shepherd Dog Club of America, the club was renamed White Shepherd Club of Canada in 1973. Its first conformation show was held that year with 8 dogs entered and 25 people in attendance. In Canada, the (CKC) is incorporated under the Animal Pedigree Act, a federal statute under the auspices of the Ministry of Agriculture, which is the governing body that sets down recognition and standards for all pure animal breeds.
For a long time, Agriculture Canada had protected white German Shepherds from the many attempts by the German Shepherd Dog Club of Canada to have white dogs disqualified from the CKC conformation ring, as had long been the case in the USA. Some brave members of WSCC had shown in the CKC breed rings and had even accumulated points toward their dogs' CKC Championships.
That all changed in 1998, when the color white was officially disqualified from the CKC German Shepherd breed standard. 15-week-old White Shepherd Disappointed but undeterred, the WSCC continues to work toward full breed recognition of the White Shepherd as a separate breed with the CKC. The club hosts shows several times a year, often in combination with the. Event dates and locations are published in the club's newsletter and on its web site. In September 1995, a small group of fanciers of the white-coated German Shepherd Dog established the American White Shepherd Association (AWSA), a new club to advance, promote and protect the White Shepherd breed in the United States. In cooperation with the White Shepherd Club of Canada, AWSA wrote and published a new breed standard, and eventually petitioned the American Kennel Club for full recognition as a unique pure breed, separate from and independent of the German Shepherd Dog. As of this writingAKC has not granted recognition or registration for the White Shepherd breed, but the breeders, fanciers and members of AWSA carry on with independently-held club activities as well as running and maintaining the private club registry.
AWSA continues to negotiate with the AKC for breed recognition as well as with the German Shepherd Dog Club of America (GSDCA) for breed separation. Until such time as GSDCA can be persuaded to grant official release of the white dogs, AKC must continue to register all white German Shepherd Dogs born from two AKC-registered German Shepherd parents as German Shepherd Dogs. In 1999, a group of AWSA members organized and established the United White Shepherd Club (UWSC) as a United Kennel Club affiliated parent club. They immediately petitioned for a new White Shepherd breed classification within UKC. The United Kennel Club accepted the UWSC's petition and created a new and separate White Shepherd breed conformation standard and registry. The White Shepherd breed was officially recognized by UKC on April 14, 1999. Today, United Kennel Club recognizes both the White Shepherd breed standard as well as the original German Shepherd Dog breed conformation standard where white and colored dogs continue to be considered together as one breed.
Neither UKC- nor AWSA-registered White Shepherds can be registered as FCI White Swiss Shepherd Dogs ( Berger Blanc Suisse). Breed clubs associated with each of these unique breed lines maintain their own breed standards for appearance and temperament. The breed 'appearance' standard given below is appropriate to the UKC-registered White Shepherd Dog and, with a few very minor changes - mostly in wording and layout - to the written standard of the AWSA club as well.
No matter which country they hail from, White Shepherds excel in performance events such as competition obedience and rally obedience, tracking, flyball and agility. Many fine dogs have also earned titles in herding, proving that the herding instinct and ability has been retained in this versatile breed. Appearance The White Shepherd is a direct descendant of the German Shepherd Dog and the two breeds share common roots and are similar in appearance.
However, the White Shepherd evolved from a continuous selection for a working companion dog with that exclusive color, beauty and elegance as seen both standing and in motion. Its high degree of intelligence and sense of loyalty have allowed it to become one of the most versatile working dogs (as well as pets) in existence. The White Shepherd, as recognized by UKC, is a medium-sized, well-balanced, muscular dog, slightly longer than tall, with a medium length, pure white coat, erect ears, and a low-set natural tail that normally reaches to the hock and is carried in a slight curve like a saber.
The White Shepherd is solid without bulkiness and should be shown in lean, hard physical condition. The outline of the White Shepherd is made up of smooth curves rather than angles.
When trotting, the White Shepherd moves with a long, efficient stride that is driven by a powerful forward thrust from the hindquarters. The rear leg, moving forward, swings under the foreleg and touches down in the place where the forefoot left an imprint.
Sex differences are readily apparent. The male breeds frame is often much larger than its female counterpart. The White Shepherd should be evaluated as an all-around working dog, and exaggerations or faults should be penalized in proportion to how much they deviate from breed type and how much they interfere with the dog's ability to work.
The head is proportional to the size of the dog. Males appear masculine without coarseness, and females feminine without being overly fine. The skull and muzzle are of equal length, parallel to one another, and joined at a moderate stop. There is little or no median furrow. A 1-year-old White German Shepherd dog ready for a command in the woods The White Shepherd has a weather-resistant double coat.
The outer coat is dense, straight, harsh, and close lying. The undercoat is short, thick, and fine in texture. At the neck, the coat may be slightly longer and heavier, particularly in males. Ideal coat color is a pure white. Colors ranging from a very light cream to a light biscuit tan are acceptable but not preferred.
It is a disqualification for dogs to have noses not predominantly black. The tail is set on low in a natural extension of the sloping croup. The tail extends at least to the hock joint and usually below. The appearance standard for United Kennel Club registered dogs is very similar to but not exactly the same as for other separate breed lines such as the AWSA-registered White Shepherd or the FCI internationally recognized Berger Blanc Suisse (White Swiss Shepherd Dog).
While all of the existing breed lines have a common genetic heritage with the white-coated members of the German Shepherd Dog breed, they are each separately registered with their respective clubs or registries which also maintain the individual breed appearance standards. White Shepherds are often known to constant heavy shedding. Temperament The White Shepherd has a distinct personality marked by self-confidence. The breed is poised, but when the situation demands, they are eager, alert and ready to serve in any capacity. White Shepherds demonstrate both herding and protective instincts.
With those they know, the White Shepherd is open and friendly. With strangers, they are observant and may be somewhat aloof but not apprehensive. They enjoy running, playing fetch or any activity with their human family.
This is a joyful, active, intelligent and easy to train working dog with the ability to adapt and integrate to all kinds of social events and situations. Timidity in a mature dog or aggressive behavior is not typical of this breed. White Shepherds are very loyal and tend to be especially protective of the young of various species.
Although personality is dependent on the dog, it's common for them to be whiny yet very clever and persistent. With their playful and curious personalities, they make wonderful companions although some do have the tendency toward being quite vocal by exhibiting whining, grunting, moaning and sometimes howling. Activities The White Shepherd can compete in trials, and events. Instincts and trainability can be measured at noncompetitive herding tests.
White Shepherds that exhibit basic herding instincts can be trained to compete in herding trials. Genetics.
White Shepherd performing in There are many misconceptions about white-coat German Shepherd Dogs and the gene that expresses for their coat color. Little's The Inheritance of Coat Color in Dogs hypothesized that dilution or partial ce, ca and cch of the so-called (C) gene caused the cream and white coat color variants in domestic dogs. Little's hypothesized partial albinism explanation for cream and white colored coats has been applied across most domestic dog breeds, including white coat dogs from German Shepherd breed lines, since Little first published his book. However, comparative analysis of the dog and specific breed sequences now shows that Little's hypothesized gene (C) color dilution explanation for cream and white colored coats is most likely not a relevant determinant of cream and white coats known to commonly occur in many dog breeds. Little's 1957-era partial albinism dilution explanation, as applied to explain domestic dog white and cream coat colors, can be replaced by the findings of modern genetic research.
Research has shown that a recessive e allele at the Extension (E) gene is at least partially responsible for cream and white coat color. The (E) gene, now identified as the (MC1R) gene, is one of the two genes known to code for alleles that are absolutely fundamental to the formation of all German Shepherd Dog colored coat variations. When the recessive allele is inherited from each breeding pair parent, the e/e offspring of certain breeds, including white coat dogs from German Shepherd breed lines, always have cream or white colored coats.
White Shepherds were once blamed for color dilution or paling for the entire breed because the recessive e allele of the MC1R (E) gene locus masks expression of alleles at other gene loci that actually do code for lighter (often termed as diluted or pale) colors of silver, black and tan or liver. German breeders of the 1920s and 1930s misinterpreted pale-colored offspring of white dogs as an undesirable 'white' genetic trait. A dog of normal color paired with a white GSD always produces full colored puppies because the e allele is recessive. See also. References.
Horowitz, George (1927). The Alsatian Wolf-Dog: Its origin, history, and working capabilities 2nd ed. Manchester: Our Dogs Publ.
Willis, Malcolm (1977). The German Shepherd Dog, Its History, Development, and Genetics.
New York: ARCO Pub. Rankin, Calumn (2002). The All-White Progenitor: German Shepherd Dogs.
Upfront Publishing. American White Shepherd Association, United White Shepherd Club, and White Shepherd Club of Canada. Retrieved 2007-08-03.
Hartnagle-Taylor, Jeanne Joy; Taylor, Ty (2010). Stockdog Savvy. Alpine Publications. Schmutz SM; Berryere TG. (July–August 2007). Journal of Heredity.
98 (5): 544–8. Handley, M. White Shepherd Genetics Project.
Retrieved 2007-11-19. Further information. Neufeld, Peter (1970).
The Invincible White Shepherd. Minnedosa: Glendosa Research Center.
Willis, Malcolm (1992). The German Shepherd Dog. New York: Howell Book House. Willis, Malcolm (1989). Genetics of the Dog.
New York: Howell Book House. Strickland, Winifred (1988). The German Shepherd Today / Winifred Gibson Strickland and James Anthony Moses. New York: New York: Macmillan. Ruvinsky, Anatoly (2001). The Genetics of the Dog.
Wallingford: CABI Pub. Isabell, Jackie (2002). Genetics: an Introduction for Dog Breeders. Loveland: Alpine Blue Ribbon Books. Raisor, Michelle (2005).
Determining the Antiquity of Dog Origins: Canine Domestication as a Model for the Consilience between Molecular Genetics and Archaeology. Oxford: Archaeopress. Hart, Ernest (1988). This Is the German Shepherd. Neptune City: TFH Publications. Dodge, Geraldine R (1956).
The German Shepherd Dog in America. Hart, Ernest H (1968).
Encyclopedia of dog breeds: Histories and official standards: evolution, genealogy, genetics, husbandry, etc. Crown Publishers. Goldbecker, William (1955). This is the German Shepherd. Practical science Pub Co.
Reeves, Jean (2007). White Shepherd.
Kennel Club Books, Inc. Schmutz SM, Berryere TG (July–August 2007). Journal of Heredity. 98 (5): 544–8. Kerns JA, Olivier M, Lust G, Barsh GS (2003). 'Exclusion of melanocortin-1 receptor (mc1r) and agouti as candidates for dominant black in dogs'. Journal of Heredity.
94 (1): 75–9. External links Wikimedia Commons has media related to.
A loss of genetic diversity may lead to increased disease risks in subpopulations of dogs. The canine breed structure has contributed to relatively small effective population size in many breeds and can limit the options for selective breeding strategies to maintain diversity.
With the completion of the canine genome sequencing project, and the subsequent reduction in the cost of genotyping on a genomic scale, evaluating diversity in dogs has become much more accurate and accessible. This provides a potential tool for advising dog breeders and developing breeding programs within a breed. A challenge in doing this is to present complex relationship data in a form that can be readily utilized. Here, we demonstrate the use of a pipeline, known as NetView, to visualize the network of relationships in a subpopulation of German Shepherd Dogs. Introduction The genetic composition of a breed determines the physical and physiological parameters that make up individuals. Studies have shown that there is a loss of the total amount of genetic polymorphism, generally referred to as genetic diversity, in modern dog populations. Genetic diversity has been affected by population bottlenecks as dogs were domesticated from the wild population, and again through selection for breed type.
In particular, purebred dogs have been selectively bred and, in some lines, closely bred with the dominant use of popular sires, resulting in a reduction of genetic diversity. This is revealed by the presence of strong selection signatures when comparing dog genotypes from different breeds., For purebred dogs, this has been influenced by morphological criteria, as defined by breed standards, and by the dominant influence of champion show dogs. Overall, the loss of diversity is estimated to be 90% compared to ancestral dog populations, prompting calls for the use of the remaining diversity for maintaining health., The canine genome sequencing project has generated a greater understanding of genomic structure and variation within and between dog breeds. – It has also enabled the generation of genomic tools to measure metrics across the genome scale, providing detailed insight into genome function, – genetic diversity, – and inherited disorders. – Diversity can be measured using the calculations of population parameters such as “effective population size,” which estimate the equivalent number of individuals contributing to the breeding population that would give rise to the observed variance in gene frequency and inbreeding rate in the population. The larger the effective population size, the greater the predicted diversity. With the advent of low-cost genotyping, molecular data are much more readily available and accessible to measure diversity accurately.
However, devising ways to present such high content data in a digestible and effective form, so that they are easily interpreted and applied, is a challenge. One way to do this is to use a visual representation based on network analysis, which has the capacity to provide an intuitive approach to interact with complex data. The German Shepherd Dog (GSD) is the largest breed (purebred) dog population in Australia and is very popular worldwide. Originally used as a herding dog, it has found widespread value as a working dog and as a pet. Using genome-wide genotyping data from a subpopulation of GSD as an example, this study employed the NetView pipeline, a bioinformatic tool developed for livestock and with broad potential utility, to visualize a network that represents individual relationships in a subpopulation of GSD. Study animals The dogs selected for this study were all purebred GSDs from Australia. Animals were identified for the study through the German Shepherd Dog League of New South Wales (NSW) and at National Championship Shows.
A total of 82 dogs (28 males and 54 females) from 50 different kennels, aged between 1 and 10 years, were included in the analysis. All procedures were performed in accordance with the guidelines for the use of animals in this research (Animal Research Act, NSW, Australia) and were approved by the Animal Ethics Committee of University of Sydney under protocols 444 and 4949.
Owners of all dogs provided written informed consent. Homozygosity and inbreeding coefficient calculation Quality control filtering was performed using the PLINK version 1.07 software. The dataset was filtered to exclude individuals with 10% missing genotypes and retain SNPs with a minor allele frequency (MAF) 0.05 and SNPs with a 90% genotyping rate. Multilocus heterozygosity (MLH), runs of homozygosity (ROH), and inbreeding were also computed in PLINK version 1.07. ROH in the genomes of the 82 individuals were identified using the homozyg command and the parameters homozyg-window-het 1, homozyg-snp 100, homozyg-window-snp 50, homozyg-window-missing 5, homozyg-window-threshold 0.05, homozyg-kb 1000, homozyg-density 50, and homozyg-gap 100, and ROH were calculated as a proportion of the canine genome. Inbreeding coefficients for genotyped dogs were calculated based on the observed versus (Hardy–Weinberg) the expected number of homozygotes.
Effective population size The effective population size ( N e) was estimated using the linkage disequilibrium method implemented by the program NeEstimator version 2.01. – To avoid bias from close linkage between loci, 10,000 evenly placed SNPs from across the genomes were selected for inclusion in the N e calculation. The genome was divided into 10,000 segments and one SNP with the highest MAF selected from each segment; the lowest frequency alleles were screened out with an MAF cutoff set at 0.05. Population structure Fine-scale population structure was calculated and visualized using NetView, a population analysis pipeline.
An unsupervised network clustering procedure, Super Paramagnetic Clustering (SPC), was used to create a fully connected population network in which individuals were clustered based on the genetic distance as calculated in PLINK from the SNP data. Complete linkage agglomerative clustering was used to produce a relationship matrix using the SNP data in PLINK. The distance matrix was imported into SPC and run with K = 10 and minimum cluster size = 2. The resulting binary edge file produced was combined with the relationship matrix file to generate a weighted relationship matrix.
The weighted relationship matrix was then converted into a GML file using the format conversion tool in Network Analysis Tools. The clustering of individuals within the network was then visualized in Cytoscape using the “organic visualization” style setting from the software options. Genotype data preparation and editing Large-scale molecular genetic data, including SNP data, must first be processed for QC and edited to remove anomalies. We used PLINK, a publically available genome analysis toolset, to identify any low call rates and duplication of samples, and to calculate allele frequencies. All 82 individual dogs had high-quality genotyping data and were included in the data analysis. From the original 173,650 SNPs present on the array, 89,265 SNPs remained following frequency and genotype pruning. Of these, 2,997 SNPs failed the missingness test (geno 0.1), while 83,641 SNPS failed the frequency test (MAF.
Homozygosity and inbreeding Based on the mean MLH value, the degree of heterozygosity in this cohort of GSD was 0.3. When considering the average of all dogs, a total of 14.16% of the genomes were covered with ROH 1 MB, with an average of 177.4 runs per dog, while only 1.61% was covered by ROH 4 MB, and 0.10% by ROH 8 MB (; ). Using data from all dogs, the effective population size ( N e) was calculated to be 43. Furthermore, when the molecular data was used to assess autozygosity, the F ROH for lengths 1MB averaged 0.119. Values of F ROH for other defined thresholds are listed in.
Genetic distance matrix Stratification within the 82 dogs was determined using the allele sharing distance (ASD) calculation. ASD was calculated as follows: 1 − average proportion of shared alleles. A module to help perform these calculations, based on the identity by state, is available in the PLINK tool-set.
The resulting distance matrix was used as an input for network computation and was visualized using a color-coded heat map. Pairwise genetic relationships between the 82 GSDs, based on the genome-scale data, are presented in. The diagonal represents the location of each dog compared to itself and is coded to the maximum intensity of blue to indicate identity.
Three prominent groupings are evident by shades of blue and in close alignment with the diagonal of the matrix. A commonly used method for visualizing similar data, a multidimensional scaling (MDS) plot, is also included. Network construction NetView uses unsupervised network clustering methodology, specifically SPC, implemented in the publically available software program, Sorting Points into Neighborhoods (SPIN). The SPC method is based on the physical properties of ferromagnets (the magnetic phase transitions of spin systems), but has been widely applied as a robust algorithm for analyzing gene expression profiles, phylogenetic trees, protein classification, and functional molecular networks., The GSD relationship matrix was used as an input into SPIN/SPC and run with a constant K-value of 10, and a minimum cluster size of 2. Network visualization To visualize the network, NetView incorporates the SPIN/SPC output into the Cytoscape software. Cytoscape is a flexible open-source software platform to visualize complex biomolecular network data. The resulting network is shown in.
There are three clear clusters of closely related dogs, with 11, 12, and 14 dogs identified in each of these clusters. These clusters represent the most closely related dogs within a line.
This can be compared with the relationship matrix that details the results for each of the pairwise comparisons. The other dogs are shown to be more distantly related, with varying contributions to the network. The population structure is represented in terms of nodes, edges between nodes, and thickness of edges. Represents a static and dynamic display of the network, which may be explored in detail. A static example of a zoomed view of one region of the network is shown in. The network may also be scaled to incorporate additional genetic data or to add annotations or other types of relevant data. For example, a weighting may be included for gene coexpression data.
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Discussion Genome diversity is directly relevant to maintain a healthy breed and reduce morbidity from inherited disorders in dogs. Geneticists use measures of inbreeding and ROH as estimates of population-based descriptions of homozygosity. However, inbreeding averages do not capture risk to individuals very well and even ROH can be poorly correlated with disease prevalence, especially if based on common SNPs. This may be confusing when applied to breeding programs. Visualization can reflect accurate relationships and provide a tool for mate selection in a relatively simple manner. We have adopted the tools that are described as NetView, a pipeline approach to construct a relationship network.
This study demonstrates the application of NetView to visualize the genomic diversity in a cohort of GSD. Maintenance of breed genetic diversity in dog breeds is a key goal for promoting health and welfare of animals.
Different methods for measuring diversity have been developed based on genealogical and molecular data. Average values for coefficients of inbreeding are often quoted when discussing reduced diversity, and with the availability of molecular data, direct measures of genetic heterogeneity, or its converse, ROH, may be considered. ROH are classified according to the length of the observed homozygosity, with short runs reflecting more ancient haplotypes and long runs reflecting likely close relationships between parents. Long runs of ROH are enriched for deleterious mutations. Measured at a breed level, these parameters do not necessarily correlate with diseases across the entire breed, but the probability of inherited diseases arising in subpopulations of the breed is increased. Bateson and Sargan estimated that, in a breed with a recessive disease allele frequency of 10%, a 13% reduction in heterozygosity translates to 1.2% increase in the prevalence of an inherited disease. Within a breed, there is a limit to the available genetic diversity, which may be measured as the effective population size and is related to the ancestral founder population and the selective breeding effects over the intervening period.
However, for purebred dogs, these practices have resulted in some very complex pedigree structures. Commonly, the complexity and reduced diversity arises from the limited use of breeding dogs, with preference given to the use of champion sires or selected dogs with desirable conformational features. As a result pronounced sire effects, such as increased inbreeding, may be restricted to subpopulations within the breed. The simplest advice for breeders has been to avoid mating dogs that are close relatives. Adopting this approach beyond the immediate family can be difficult to determine, and simply minimizing coancestry may have a little effect on the breed diversity over the longer term. With the introduction of increasing levels of available molecular data for individual dog genomes, either as a complete sequence or genome-wide SNP genotyping, the potential to identify disease-causing mutations has grown markedly.
This information is now incorporated into breed health strategies for registered dogs and is helping in the decision of managing allele frequencies in the population via DNA testing and avoiding carrier matings, or even breeding to eliminate the mutation entirely, although the latter approach needs to be carefully considered to offset potential loss of diversity. With the expansion of molecular data, the capacity to accurately calculate relationships is also markedly enhanced. These data provide another level of information for breeders and hold the potential for improved choice of mating pairs when compared with simply not mating close relatives. Molecular data provide the means to calculate the actual genetic similarity of dogs, independent of geographic location and the extent of pedigree information. However, simplifying the data to present an overview of complex relationship or pedigree information is a challenge. One approach has been adopted to develop computer-based algorithms.
Windig and Oldenbroek developed a computer-based simulation program to manage inbreeding at a national level for Golden Retrievers in the Netherlands. Others have developed breeding values for complex traits using traditional methods of estimated breeding values to incorporate into breeding decisions for specific disorders. – Such programs need to have oversight, since selection based on individual traits can lead to unintended adverse consequences. Despite this potential drawback, the availability of a single numerical measure of a complex trait has proven to be highly valuable for selective breeding in livestock species. However, when choosing mates simply to maintain diversity, a simple visual method to identify the degree of genetic similarity may also be beneficial, such as a network view, as demonstrated in this study.
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Visualization reflects an accurate measure of the relationship between two animals from molecular data. Typically, this creates a complex matrix or analysis that is difficult to represent in a simple format. Visualization of complex data has the advantage of providing an immediate source of information on the diversity spectrum across a subpopulation or even across the entire population of extant dogs within a breed. Interpretation of the visualized data is intuitive, and the network may be presented in a dynamic form to allow for exploration of an additional level of detail. The NetView approach has the advantage of providing a pipeline protocol using free software modules. The application of the pipeline to the GSD data in this article demonstrates the step-by-step procedures. Now, this analysis pipeline has also been implemented in Python.
ACADEMIC EDITOR: J. Efird, Associate Editor PEER REVIEW: Four peer reviewers contributed to the peer review report.
Reviewers’ reports totaled 1860 words, excluding any confidential comments to the academic editor. FUNDING: This work was supported in part by the Canine Research Foundation.
SM was the recipient of an Australian Postgraduate Research Scholarship; HM was the recipient of an Endeavour International Postgraduate Research Scholarship, an International Postgraduate Award from the University of Sydney, and a Goldie and Susie Lesue Scholarship from the University of Sydney’s Postgraduate Research Support Scheme. The authors confirm that the funders had no influence over the study design, content of the article, or selection of this journal. COMPETING INTERESTS: Authors disclose no potential conflicts of interest. Paper subject to independent expert blind peer review. All editorial decisions made by independent academic editor.
Upon submission manuscript was subject to anti-plagiarism scanning. Prior to publication all authors have given signed confirmation of agreement to article publication and compliance with all applicable ethical and legal requirements, including the accuracy of author and contributor information, disclosure of competing interests and funding sources, compliance with ethical requirements relating to human and animal study participants, and compliance with any copyright requirements of third parties. This journal is a member of the Committee on Publication Ethics (COPE). Author Contributions Conceived and designed the experiments: SM, HM, MK, PW. Analyzed the data: SM, RB, MK, PW.
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Wrote the first draft of the manuscript: SM, RB, PW. Contributed to the writing of the manuscript: SM, RB, HM, MK, PW.
Agree with the results and conclusions: SM, RB, HM, MK, PW. Jointly developed the structure and arguments for the paper: SM, RB, MK, PW. Made critical revisions and approved final version: SM, RB, MK, PW. All authors reviewed and approved of the final manuscript.