SNP AND GENETIC ASSOCIATIONS OF CANINE TRAITS, DISEASE, AND OTHER PHENOTYPES Inventor: Yalda Zare SEQUENCE LISTING [0001] The present application includes a Sequence Listing in electronic format as a XML> file entitled “P13941WO00_2022-09-30_SYNO_S1050-000014_SEQLIST_ST26_v1,� �� which was created on September 30, 2022, which has a size of 278 KB (285,536 bytes), (measured in MS-Windows), and which is incorporated herein by reference in its entirety. BACKGROUND OF THE DISCLOSURE Technical Field [0002] The present disclosure relates, generally, to improved GWAS methodologies that employ multi-locus associations to account for kinship and/or population structure and multiple testing correction. Provided are methods, including computer-implemented methods, for identifying in a canine subject a predisposition for canine hip dysplasia (CHD), canine elbow dysplasia (CED), excessive fur shedding, or elevated weight gain. Also provided are genetic markers and diagnostic chips and/or tests for identifying SNPs or other mutations in a gene that are predictive in a canine subject of a predisposition for canine hip dysplasia (CHD), canine elbow dysplasia (CED), excessive fur shedding, or elevated weight gain. Description of the Related Art [0003] Canine hip dysplasia (CHD) and canine elbow dysplasia (CED) are among the most common inherited polygenic orthopedic trait in dogs, also influenced by environmental factors (such as sex, age, and body weight). CHD and CED are more prevalent in large and giant breeds of dogs often resulting in mild or no clinical signs. Diagnosis is confirmed radiographically by evaluating signs of degenerative joint disease, incongruence, and/or passive hip joint laxity. Heritability estimates for CHD vary from 0.1 to 0.83, due to different pedigrees, methods used to calculate the heritability, and the hip phenotypes analyzed. [0004] There are no ideal medical or surgical treatments for CHD or CED, so prevention based on controlled breeding and proactive management of high-risk animals such as lifestyle choices, food decisions and surgeries is the optimal approach. Programs based on selection of dogs with better individual phenotypes for breeding are effective when strictly applied but remain inferior to the selection of dogs based on estimation of breeding values. Recommended method to improve hip quality in controlled breeding schemes (higher selection pressure) would be based on the estimation of genomic estimated breeding values (GEBVs). See, Ginja et al., Vet. Med. (Auckl) 6:193-202 (2015) and Eynard et al., G38:113 (2018). The Impact of genomic selection against hip dysplasia has been reported for the Labrador Retriever. Sanchez-Molano, J. Animal Breeding and Genetics 131(2):134-145 (2014). [0005] Canine fur shedding and individual body weight are some of the most important traits in dogs for owners. While shedding is the natural process of losing old or damaged dog hair, the amount and frequency of shedding depends upon a dog’s health and breed. Excessive canine shedding can also be symptomatic of parasite, fungal or bacterial infections, kidney disease, pregnancy, cancer, immune system disorders, and poor nutrition. [0006] Three genes (RSPO2, FGF5, and KRT71) have been identified that are associated with variation in hair coat length, hair conformation, and degree of shedding. A variant in the RSPO2 gene is associated with low-shedding wiry coats (like poodles), FGF5 corresponds to a short or long hair coat, and KRT71 correlates with a curly hair coat. Cadieu et al., Science 326:150-153 (2009). Shorter hair breeds such as Basset Hounds have normal copies of all three genes, while long hair breeds, like Golden Retrievers, have a variant of FGF5. Airedale terriers have variants in KRT71 and RSPO2, which causes a short but curly and wiry coat. Kang, Genes 13(1):102 (2022). [0007] A fourth gene, MC5R, was identified through a Genome-Wide Association Study, which employed a Mixed Linear Model (MLM) methodology and accounted for kinship (i.e., the genetic relatedness between individual dogs) through a single-locus association study that looked at the association of a given trait with individual genetic markers (SNPs). Hayward et al., Nature Communications 10460 (2016). The MC5R gene is conserved across all mammals, expressed in sebaceous glands, and involved in the production of sebum, which affects water repellency and thermo-regulation and suggests a connection between sebum production and shedding in dogs. [0008] Canine obesity is associated with reduced lifespan and morbidity. It has been reported that, in developed countries, the prevalence of canine obesity ranges between 34% and 59% (Colliard et al., J. Nutr.136 (Suppl 7):1951S-1954S (2006). While weight gain in dogs is often attributed to environmental factors including reduced exercise and consumption of high-calorie food, the susceptibility to obesity varies between dog breeds, which suggests that genetic factors influence the onset of canine obesity. In a study on obesity in Labrador retrievers, a 14 bp deletion in proopeiomelanocortin (POMC) was identified that disrupts ß-MSH and ß-endorphin coding sequences and is associated with body weight, adiposity, and greater food consumption. Raffan et al., Cell Metabolism 23(5):893 (2016). [0009] Canine obesity is also associated with a heightened susceptibility to diabetes mellitus (DM). Breeds vary is susceptibility to DM indicating that genetic factors are likely involved in disease susceptibility (Davison et al., J. Small Anim. Tract.46(9):464 (2005), Davison et al., Vet Rec 156(15):467-71 (2005), Catchpole et al., Diabetologia 48(10):1948-56 (2005), and Heeley et al., Canine Med. and Genetics 7(6) (2020). [0010] While genotyping and high-throughput sequencing technologies have been employed to identify genetic factors associated with canine hip dysplasia, elbow dysplasia, fur shedding, obesity, and diabetes and despite recent advancements in the identification of single-nucleotide polymorphisms, genes, and pathways associated with canine traits, disease, and other phenotypes, there remains a substantial unmet need for sensitive methodologies for identifying candidate SNPs and genes for use in predicting phenotype and developing therapeutically effective modalities for the prevention, treatment, and control of canine phenotypes. SUMMARY OF THE DISCLOSURE [0011] The present disclosure fulfills unmet needs in the art by providing improved GWAS methodologies that employ multi-locus associations, which account for kinship and/or population structure, and a multiple testing correction approach. Within certain aspects of these GWAS methodologies multi-locus associations are achieved by using a Multiple Loci Mixed Linear Model (MLMM) that incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. [0012] Thus, provided herein are novel SNPs, genes and genetic pathways that are highly predictive of, respectively, canine hip dysplasia (CHD), canine elbow dysplasia (CED), canine fur shedding, and canine individual weight. The SNP, gene and genetic pathway lists disclosed herein exhibit surprising advantages in trait prediction and modelling over those that are currently disclosed and additionally provide target list for further discovery of treatment paths. [0013] Within certain embodiments, the present disclosure provides methods for identifying in a canine subject a predisposition for canine hip dysplasia (CHD), wherein (a) genotype data is obtained for a canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4), which are associated with canine hip dysplasia (CHD); and (b) identifying in the one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting CHD. [0014] Within other embodiments, the present disclosure provides methods for identifying in a canine subject a predisposition for canine elbow dysplasia (CED), wherein (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12), which are associated with canine elbow dysplasia (CED); and (b) identifying in the one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CED. [0015] Within further embodiments, the present disclosure provides methods for identifying in a canine subject a predisposition for excessive fur shedding, wherein (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16), which are associated with canine fur shedding; and (b) identifying in the one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting excessive fur shedding. [0016] Withing still further embodiments, the present disclosure provides methods for identifying in a canine subject a predisposition for elevated weight gain, wherein (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27), which are associated with a predisposition for elevated weight gain; and (b) identifying in the one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting elevated weight gain. [0017] In other embodiments, the present disclosure provides computer-implemented methods for determining in a canine subject a predisposition for canine hip dysplasia (CHD), wherein (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4), which are associated with canine hip dysplasia (CHD); and (b) applying a trained machine learning classifier to the genotype data to determine a predicted canine hip dysplasia (CHD) phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNPs) or other mutations that is predictive of a predisposition in the canine subject for developing or exhibiting CHD. [0018] In yet other embodiments, the present disclosure provides computer-implemented methods for determining in a canine subject a predisposition for canine elbow dysplasia (CED), wherein (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12), which are associated with canine elbow dysplasia (CED); and (b) applying a trained machine learning classifier to the genotype data to determine a predicted canine elbow dysplasia (CED) phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting CED. [0019] Within further embodiments, the present disclosure provides computer-implemented methods for determining in a canine subject a predisposition for excessive fur shedding, wherein (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16), which are associated with canine fur shedding; and (b) applying a trained machine learning classifier to the genotype data to determine a predicted excessive fur shedding phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting excessive fur shedding. [0020] Within still further embodiments, the present disclosure provides computer- implemented methods for determining in a canine subject a predisposition for elevated weight gain, wherein: (a) genotype data is obtained for the canine subject comprising the nucleotide sequence of one or more gene(s) selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27); and (b) applying a trained machine learning classifier to the genotype data to determine a predicted elevated weight gain phenotype based at least in part on the quantitative values of the single- nucleotide polymorphisms (SNPs) or other mutations in a coding region of said gene(s), which results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product, wherein the altered activity of the gene product is causative of, or contributes to the onset of, elevated weight gain and wherein the presence of the SNP or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting elevated weight gain. [0021] Within other embodiments, the present disclosure provides genetic markers that are predictive in a canine subject of a predisposition for canine hip dysplasia (CHD), wherein the genetic marker comprises a nucleotide sequence of one or more gene(s) selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting CHD. [0022] Within yet other embodiments, the present disclosure provides genetic markers that are predictive in a canine subject of a predisposition for canine elbow dysplasia (CED), wherein the genetic marker comprises a nucleotide sequence of one or more gene(s) selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting CED. [0023] Within further embodiments, the present disclosure provides genetic markers that are predictive in a canine subject of a predisposition for excessive fur shedding, wherein the genetic markers comprise a nucleotide sequence of one or more gene(s) selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting excessive fur shedding. [0024] Within still further embodiments, the present disclosure provides genetic markers that are predictive in a canine subject of a predisposition for elevated weight gain, wherein the genetic markers comprise a nucleotide sequence of one or more gene(s) selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting elevated weight gain. [0025] Within other embodiments, the present disclosure provides diagnostic chips and/or tests for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing canine hip dysplasia (CHD), wherein the gene is selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting. [0026] Within yet other embodiments, the present disclosure provides diagnostic chips and/or tests for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing canine elbow dysplasia (CED), wherein the gene is selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting CED. [0027] Within further embodiments, the present disclosure provides diagnostic chips and/or tests for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing excessive fur shedding, wherein the gene is selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting excessive fur shedding. [0028] Within still further embodiments, the present disclosure provides diagnostic chips and/or tests for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing elevated weight gain, wherein the gene is selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in the canine subject for developing or exhibiting elevated weight gain. [0029] These and other related aspects of the present disclosure will be better understood in light of the following drawings and detailed description, which exemplify certain aspects of the various embodiments. BRIEF DESCRIPTION OF THE DRAWINGS [0030] Certain aspects of the present disclosure will become more evident in reference to the drawings, which are presented for illustration, not limitation. [0031] FIG. 1 is a Manhattan plot of a GWAS according to the present disclosure, which considers the joint effect of multiple SNPs and, thereby, to identify common genetic variants that are strongly associated with, and likely causative of, canine hip dysplasia (CHD). [0032] FIG.2 is a Q-Q plot of SNPs associated with canine hip dysplasia (CHD). [0033] FIG.3 is a GO-Term enrichment plot for Canine Hip Dysplasia (CHD). [0034] FIG. 4 is a Manhattan plot of a GWAS according to the present disclosure, which considers the joint effect of multiple SNPs and, thereby, to identify common genetic variants that are strongly associated with, and likely causative of, canine elbow dysplasia (CED). [0035] FIG.5 is a Q-Q plot of SNPs associated with canine elbow dysplasia (CED). [0036] FIG.6 is a GO-Term enrichment plot for Canine Elbow Dysplasia (CED). [0037] FIG. 7 is a Manhattan plot of a GWAS according to the present disclosure, which considers the joint effect of multiple SNPs and, thereby, to identify common genetic variants that are strongly associated with, and likely causative of, canine fur shedding. [0038] FIG.8 is a Q-Q plot of SNPs associated with canine fur shedding. [0039] FIG.9 is a GO-Term enrichment plot for canine fur shedding. [0040] FIG. 10 is a Manhattan plot of a GWAS according to the present disclosure, which considers the joint effect of multiple SNPs and, thereby, to identify common genetic variants that are strongly associated with, and likely causative of, canine individual weight. [0041] FIG.11 is a Q-Q plot of SNPs associated with canine individual weight. DETAILED DESCRIPTION [0042] The present disclosure is directed to improved GWAS methodologies that employ multi-locus associations, which account for kinship and/or population structure, and a multiple testing correction approach. Within certain aspects of these GWAS methodologies multi-locus associations are achieved by using a Multiple Loci Mixed Linear Model (MLMM) that incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. [0043] To completely eliminate the confounding, MLMM is divided into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM), which are used iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting in FEM, the associated markers are estimated in REM by using them to define kinship. The p-values of testing markers and the associated markers are unified at each iteration. [0044] The presently-disclosed GWAS methodologies optimize signal to noise ratio by controlling false negatives and false positives to, thereby, increase both specificity and sensitivity. By repeating the association testing procedures as many times as the number of SNPs in the data (i.e. for a data set comprising 100,000 SNPs, association tests are repeated 100,000 times) false positives are controlled. The present methodologies also overcome limitations in existing multiple-testing approaches, which are excessively stringent and, therefore, lose a true signal and yield a high number of false negatives or that are insufficiently stringent and yield a high number of false positives. The present methodologies also avoid spurious associations that are exhibited by existing methodologies that cluster different groups sharing the same ancestry or that are from the same breed, which lead to spurious associations if not properly accounted for. Moreover, the present methodologies overcome limitations in existing single-locus associations that ignore the correlation of SNPs and, consequently, lose true signals or incorrectly identify the wrong loci as significant. [0045] Thus, provided herein are novel SNPs, genes and genetic pathways that are highly predictive of, respectively, canine hip dysplasia (CHD), canine elbow dysplasia (CED), canine fur shedding, and canine individual weight. The SNP, gene and genetic pathway lists disclosed herein exhibit surprising advantages in trait prediction and modelling over those that are currently disclosed and additionally provide target list for further discovery of treatment paths. [0046] Within certain embodiments, the present disclosure provides methods for identifying in a canine subject a predisposition for canine hip dysplasia (CHD), canine elbow dysplasia (CED), excessive fur shedding, or elevated weight gain. In other embodiments, the present disclosure provides computer-implemented methods for determining in a canine subject a predisposition for canine hip dysplasia (CHD), canine elbow dysplasia (CED), excessive fur shedding, or elevated weight gain. In further embodiments, the present disclosure provides genetic markers that are predictive in a canine subject of a predisposition for canine hip dysplasia (CHD), canine elbow dysplasia (CED), excessive fur shedding, or elevated weight gain, In still further embodiments, the present disclosure provides diagnostic chips and/or tests for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing canine hip dysplasia (CHD), canine elbow dysplasia (CED), excessive fur shedding, or elevated weight gain. [0047] These and other aspects of the present disclosure can be better understood by reference to the following non-limiting definitions. Definitions [0048] As used herein, the terms “single-nucleotide polymorphism” and “SNP” refer interchangeably to a germline substitution of a single nucleotide at a specific position in the genome. For example, within a certain gene, a G nucleotide may appear at a given position in a majority of individuals, but an A nucleotide may appear at the same position in a minority of individuals. Thus, in this example, the nucleotide position comprises a “single-nucleotide polymorphism” or “SNP” and the two possible nucleotide variations (i.e. G or A) are referred to as the alleles for this specific position. See, Monga et al., G37(9):2931-2943 (2017). [0049] As used herein, the terms “genome-wide association study” and “GWAS” refer interchangeably to the determination of whether a genetic variant (i.e. a single-nucleotide polymorphism” or “SNP”), gene, or genetic pathway is associated with a particular disease, trait, or other phenotype. Zhang, Genome Research 14(5):908-16 (2004) and Visscher, Genetics 101(1):5-22 (2017). “Genome wide association studies (GWAS) are computationally demanding analyses that use large sample sizes and dense marker sets to discover associations between quantitative trait variation and genetic variants.” Kusmec, ASPB (2018). [0050] As used herein, the term “Manhattan plot” refers to a type of plot used to display data with a large number of data-points, many of non-zero amplitude, and with a distribution of higher- magnitude values. The plot is commonly used in genome-wide association studies (GWAS) to display significant single-nucleotide polymorphisms (SNPs). Its name derives from the similarity of such a plot to the Manhattan skyline. In GWAS, Manhattan plots, genomic coordinates are displayed along the x-axis, with the negative logarithm of the association p-value for each single nucleotide polymorphism (SNP) displayed on the y-axis, meaning that each dot on the Manhattan plot signifies a SNP. Because the strongest associations have the smallest p-values (e.g., 10 ⁻¹⁵ ), their negative logarithms will be the greatest (e.g., 15). The different colors of each block show the extent of each chromosome. Gibson, Nature Genetics 42(7):558-560 (2010). [0051] As used herein, the term “QQ plot” refers to a quantile-quantile plot, which is a probability plot that compares two probability distributions by plotting their quantiles against each other. Wilk, Biometrika 55(1):1-17 (1968). [0052] Unless defined otherwise, all technical and scientific terms used above have the same meaning as commonly understood by one of ordinary skill in the art to which embodiments of the present invention pertain. [0053] The term "and/or" where used herein is to be taken as specific disclosure of each of the two specified features or components with or without the other. Thus, the term and/or" as used in a phrase such as "A and/or B" herein is intended to include "A and B," "A or B," "A" (alone), and "B" (alone). Likewise, the term "and/or" as used in a phrase such as "A, B, and/or C" is intended to encompass each of the following embodiments: A, B, and C; A, B, or C; A or C; A or B; B or C; A and C; A and B; B and C; A (alone); B (alone); and C (alone). [0054] Where a term is provided in the singular, other embodiments described by the plural of that term are also provided. As used herein, the terms “include,” “includes,” and “including” are to be construed as at least having the features to which they refer while not excluding any additional unspecified features. It will be understood that, unless indicated to the contrary, terms intended to be "open" (e.g., the term "including" should be interpreted as "including but not limited to," the term "having" should be interpreted as "having at least," the term "includes" should be interpreted as "includes but is not limited to," etc.). Phrases such as "at least one," and "one or more," and terms such as "a" or "an" include both the singular and the plural. The term “or” is synonymous with “and/or” and means any one member or combination of members of a particular list. [0055] It will be further understood that where features or aspects of the disclosure are described in terms of Markush groups, the disclosure is also intended to be described in terms of any individual member or subgroup of members of the Markush group. Similarly, all ranges disclosed herein also encompass all possible sub-ranges and combinations of sub- ranges and that language such as “between,” “up to,” “at least,” “greater than,” “less than,” and the like include the number recited in the range and includes each individual member. [0056] The term “configured” describes structure capable of performing a task or adopting a particular configuration. The term “configured” can be used interchangeably with other similar phrases, such as constructed, arranged, adapted, manufactured, and the like. Terms characterizing sequential order, a position, and/or an orientation are not limiting and are only referenced according to the views presented. [0057] The “scope” of the inventions disclosed herein are defined by the appended claims, along with the full scope of equivalents to which such claims are entitled. The scope of the invention is further qualified as including any possible modification to any of the aspects and/or embodiments disclosed herein which would result in other embodiments, combinations, subcombinations, or the like that would be obvious to those skilled in the art. Embodiments [0058] The following numbered embodiments form part of the present disclosure. [0059] 1. A method for identifying in a canine subject a predisposition for canine hip dysplasia (CHD), said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4), which are associated with canine hip dysplasia (CHD); and (b) identifying in said one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CHD. [0060] 2. The method of embodiment 1 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CHD. [0061] 3. The method of embodiment 1 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CHD. [0062] 4. A method for identifying in a canine subject a predisposition for canine elbow dysplasia (CED), said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12), which are associated with canine elbow dysplasia (CED); and (b) identifying in said one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CED. [0063] 5. The method of embodiment 4 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CED. [0064] 6. The method of embodiment 4 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CED. [0065] 7. A method for identifying in a canine subject a predisposition for excessive fur shedding, said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16), which are associated with canine fur shedding; and (b) identifying in said one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting excessive fur shedding. [0066] 8. The method of embodiment 7 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of excessive fur shedding. [0067] 9. The method of embodiment 7 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of excessive fur shedding. [0068] 10. A method for identifying in a canine subject a predisposition for elevated weight gain, said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27); and (b) identifying in said one or more gene(s) a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting elevated weight gain. [0069] 11. The method of embodiment 10 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of elevated weight gain. [0070] 12. The method of embodiment 10 wherein said SNP or other mutation is in a non- coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of elevated weight gain. [0071] 13. A computer-implemented method for determining in a canine subject a predisposition for canine hip dysplasia (CHD), said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4), which are associated with canine hip dysplasia (CHD); and (b) applying a trained machine learning classifier to the genotype data to determine a predicted canine hip dysplasia (CHD) phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNPs) or other mutations that is predictive of a predisposition in said canine subject for developing or exhibiting CHD. [0072] 14. The computer-implemented method of embodiment 13 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CHD. [0073] 15. The computer-implemented method of embodiment 13 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CHD. [0074] 16. A computer-implemented method for determining in a canine subject a predisposition for canine elbow dysplasia (CED), said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12), which are associated with canine elbow dysplasia (CED); and (b) applying a trained machine learning classifier to the genotype data to determine a predicted canine elbow dysplasia (CED) phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNPs) or other mutations that is predictive of a predisposition in said canine subject for developing or exhibiting CED. [0075] 17. The computer-implemented method of embodiment 16 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CED. [0076] 18. The computer-implemented method of embodiment 16 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CED. [0077] 19. A computer-implemented method for determining in a canine subject a predisposition for excessive fur shedding, said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16), which are associated with canine fur shedding; and (b) applying a trained machine learning classifier to the genotype data to determine a predicted excessive fur shedding phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNPs) or other mutations that are predictive of a predisposition in said canine subject for developing or exhibiting excessive fur shedding. [0078] 20. The computer-implemented method of embodiment 19 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of excessive fur shedding. [0079] 21. The computer-implemented method of embodiment 19 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of excessive fur shedding. [0080] 22. A computer-implemented method for determining in a canine subject a predisposition for elevated weight gain, said method comprising: (a) obtaining genotype data for said canine subject wherein said genotype data comprises the nucleotide sequence of one or more gene(s) selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27); and (b) applying a trained machine learning classifier to the genotype data to determine a predicted elevated weight gain phenotype based at least in part on the quantitative values of the single-nucleotide polymorphisms (SNPs) or other mutations that are predictive of a predisposition in said canine subject for developing or exhibiting elevated weight gain. [0081] 23. The computer-implemented method of embodiment 22 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of elevated weight gain. [0082] 24. The method of embodiment 22 wherein said SNP or other mutation is in a non- coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of elevated weight gain. [0083] 25. A genetic marker that is predictive in a canine subject of a predisposition for canine hip dysplasia (CHD), said genetic marker comprising: a nucleotide sequence of one or more gene(s) selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CHD. [0084] 26. Genetic marker of embodiment 25 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CHD. [0085] 27. The genetic marker of embodiment 25 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CHD. [0086] 28. A genetic marker that is predictive in a canine subject of a predisposition for canine elbow dysplasia (CED), said genetic marker comprising: a nucleotide sequence of one or more gene(s) selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CED. [0087] 29. The genetic marker of embodiment 28 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CED. [0088] 30. The genetic marker of embodiment 28 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CED. [0089] 31. A genetic marker that is predictive in a canine subject of a predisposition for excessive fur shedding, said genetic marker comprising: a nucleotide sequence of one or more gene(s) selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting excessive fur shedding. [0090] 32. The genetic marker of embodiment 31 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of excessive fur shedding. [0091] 33. The genetic marker of embodiment 31 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of excessive fur shedding. [0092] 34. A genetic marker that is predictive in a canine subject of a predisposition for elevated weight gain, said genetic marker comprising: a nucleotide sequence of one or more gene(s) selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27) that include a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting elevated weight gain. [0093] 35. The genetic marker of embodiment 34 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of elevated weight gain. [0094] 36. The genetic marker of embodiment 34 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of elevated weight gain. [0095] 37. A diagnostic chip and/or a test for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing canine hip dysplasia (CHD), wherein said gene is selected from the group consisting of SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CHD. [0096] 38. The diagnostic chip of embodiment 37 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CHD. [0097] 39. The diagnostic chip of embodiment 37 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CHD. [0098] 40. A diagnostic chip and/or a test for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing canine elbow dysplasia (CED), wherein said gene is selected from the group consisting of FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting CED. [0099] 41. The diagnostic chip of embodiment 40 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of CED. [0100] 42. The diagnostic chip of embodiment 40 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of CED. [0101] 43. A diagnostic chip and/or a test for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing excessive fur shedding, wherein said gene is selected from the group consisting of MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15) and PKHD1L1 (SEQ ID NO: 16) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting excessive fur shedding. [0102] 44. The diagnostic chip of embodiment 43 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of excessive fur shedding. [0103] 45. The diagnostic chip of embodiment 43 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of excessive fur shedding. [0104] 46. A diagnostic chip and/or a test for identifying a SNP or other mutation in a gene that is associated with and predictive of a predisposition in a canine subject for developing elevated weight gain, wherein said gene is selected from the group consisting of XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), and ATP6V0E1 (SEQ ID NO: 27) that includes a single-nucleotide polymorphism (SNP) or other mutation that is predictive of a predisposition in said canine subject for developing or exhibiting elevated weight gain. [0105] 47. The diagnostic chip of embodiment 46 wherein said SNP or other mutation is in a coding region of said gene(s) that results in a non-conservative amino acid substitution in, and alters the activity of, a corresponding gene product wherein said altered activity is causative of, or contributes to, the onset of elevated weight gain. [0106] 48. The diagnostic chip of embodiment 46 wherein said SNP or other mutation is in a non-coding region of said gene(s) that results in the over or under expression of said gene(s) wherein said over or under expression is causative of, or contributes to, the onset of elevated weight gain. * * * * * [0107] All references cited herein, whether supra or infra, including, but not limited to, patents, patent applications, and patent publications, whether U.S., PCT, or non-U.S. foreign, and all technical and/or scientific publications are hereby incorporated by reference in their entirety. EXAMPLES [0108] While various embodiments have been disclosed herein, other embodiments will be apparent to those skilled in the art. The various embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the claims. The present disclosure is further described with reference to the following examples, which are provided to illustrate certain embodiments and are not intended to limit the scope of the present disclosure or the subject matter claimed. Example 1 SNPs, Genes, and Pathways Associated with Canine Hip Dysplasia (CHD) (Working) [0109] SNPs, genes, and pathways associated with Canine Hip Dysplasia (CHD) were identified via GWAS methodologies employing multi-locus associations that accounted for kinship and/or population structure in combination with multiple testing correction. In some aspects of these GWAS methodologies, multiple testing correction was achieved via a multiple loci mixed linear model that incorporated multiple markers simultaneously as covariates to partially remove the confounding between testing markers and kinship. [0110] Table 1 discloses single-nucleotide polymorphisms (SNPs) localized to chromosomes 6, 12, 15, 27, 28, and 36, which were identified as associated with Canine Hip Dysplasia. Table 1 Canine Hip Dysplasia-associated SNPs that were identified via the GWAS Methodologies Disclosed Herein [0111] Each of the SNPs presented in Table 1 was run through a gene mapping function and mapped to the underlying genes within 2, 10, 20, 50, 100, 200, or 500 kb of those SNPs. Genes that were associated with Canine Hip Dysplasia (CHD) are summarized in Table 2. Table 2 Genes that were Associated with Canine Hip Dysplasia (CHD) through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein  [0112] Of the five genes that were associated with CHD, one gene (CTBP2) has been previously reported in the literature. Hayward et al., Nature Communications 10460 (2016). Four genes (SPACA1, MND1, SLC4A10, and DPP4) are newly identified as associated with CHD. Of those four genes, it has been reported that SLC4A10 is a sodium-coupled chloride/bicarbonate co- transporter associated with plasma osmolality and osteopetrosis (Tseng et al., Int. J. Mol. Sci. 22:4187 (2021); Boger, et al., J. Am. Soc. Nephrol. 28:2311 (2017); and Meyer et al., PLoS Genetics 6:e1001045 (2010)) and the dipeptidyl peptidase DPP4 is associated with rheumatoid arthritis (Mascolo, et al., Drug Saf.39:401-407 (2016)) in mice and humans. [0113] The nucleotide sequences of cDNAs encoded by the canine genes from Canis lupus familiaris (SPACA1 (SEQ ID NO: 1), MND1 (SEQ ID NO: 2), SLC4A10 (SEQ ID NO: 3), and DPP4 (SEQ ID NO: 4) that were newly identified as associated with Canine Hip Dysplasia are disclosed in Table 3. Table 3 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Hip Dysplasia (CHD) through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein dysplasia, lists of genes within 2, 10, 20, 50, 100, 200, or 500 kb from each of the significant SNPs were generated. The only set of genes having enriched “biological process” GO terms were those found within 50k of those SNPs. See, FIG.3. Example 2 SNPs, Genes, and Pathways Associated with Canine Elbow Dysplasia (CED) (Working) [0115] SNPs, genes, and pathways associated with Canine Elbow Dysplasia (CED) were identified via GWAS methodologies employing multi-locus associations that accounted for kinship and/or population structure in combination with multiple testing correction. In some aspects of these GWAS methodologies, multiple testing correction was achieved via a multiple loci mixed linear model that incorporated multiple markers simultaneously as covariates to partially remove the confounding between testing markers and kinship. [0116] Table 4 discloses single-nucleotide polymorphisms (SNPs) localized to chromosomes 10, 11, 26, and 35, which were identified as associated with canine elbow dysplasia. Of the four significant SNPs found, one SNP on chromosome 26 at Position 16554631 was previously identified as associated with CED. Hayward et al., Nature Communications 10460 (2016). Table 4 Canine Elbow Dysplasia-associated SNPs that were Identified via the GWAS Methodologies Disclosed Herein [0117] Each of the four SNPs presented in Table 4 were run through a gene mapping function and mapped to the underlying genes within 2, 10, 20, 50, 100, 200, or 500 kb of those SNPs. Genes that were identified as associated with canine elbow dysplasia are summarized in Table 5. Table 5 Genes that were Associated with Canine Elbow Dysplasia (CED) through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 5 Genes that were Associated with Canine Elbow Dysplasia (CED) through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein [0118] None of the eight genes identified as associated with CED have been previously reported in the literature. Each of those eight genes (FSHR, RNF10, MLEC, UNC1198, ACADS, SSR1, CAGE1, and RREB1) is newly identified as associated with CED. [0119] The nucleotide sequences of cDNA corresponding to the canine genes from Canis lupus familiaris (FSHR (SEQ ID NO: 5), RNF10 (SEQ ID NO: 6), MLEC (SEQ ID NO: 7), UNC1198 (SEQ ID NO: 8), ACADS (SEQ ID NO: 9), SSR1 (SEQ ID NO: 10), CAGE1 (SEQ ID NO: 11), and RREB1 (SEQ ID NO: 12)) that are newly identified as associated with canine hip dysplasia are disclosed in Table 6. Table 6 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Elbow Dysplasia (CED) through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 6 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Elbow Dysplasia (CED) through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein [0120] In order to identify interesting and relevant biological pathway underlying canine elbow dysplasia, lists of genes within 2 kb, 10 kb, and 50 kb from each of the significant SNPs were generated. The only set of genes having enriched “biological process” GO terms were those found within 2 kB and 10 kB of those SNPs. See, FIG.6. Example 3 SNPs, Genes, and Pathways Associated with Canine Fur Shedding (Working) [0121] SNPs, genes, and pathways associated with canine fur shedding were identified via GWAS methodologies employing multi-locus associations that accounted for kinship and/or population structure in combination with multiple testing correction. In some aspects of these GWAS methodologies, multiple testing correction was achieved via a multiple loci mixed linear model that incorporated multiple markers simultaneously as covariates to partially remove the confounding between testing markers and kinship. [0122] Table 7 discloses 18 significant single-nucleotide polymorphisms (SNPs) localized to chromosomes 1, 13, and 33, which were identified as associated with canine fur shedding. Table 7 Canine Fur Shedding-associated SNPs that were identified via the GWAS Methodologies Disclosed Herein [0123] Each of the 18 SNPs presented in Table 7 were run through a gene mapping function and mapped to the underlying genes within 2, 10, 20, 50, 100, 200, or 500 kb of those SNPs. Genes that were identified as associated with canine fur shedding are summarized in Table 8. Table 8 Genes that were Associated with Canine Fur Shedding through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein  [0124] Of the seven genes identified as associated with canine fur shedding, three genes (MC5R, RSPO2, and FGF5) have been previously reported in the literature. The MC5R gene on chromosome 1 is expressed in the hair follicle glands that produce the oily, waxy substance called sebum and the RSPO2 gene on chromosome 13 impacts hair quality. The MC5R and RSPO2 genes as well as the FGF5 gene on chromosome 32 have been identified as impacting the degree of shedding in certain dog breeds. Hayward et al., Nature Communications 10460 (2016). Genetic testing of MC5R and RSPO2 reveal the degree of shedding in a dog and can help to select dogs suitable for breeding and thus reduce shedding in puppies. Four genes (MC2R1, ANGPT1, EIF3E, and PKHD1L1), each of which is on chromosome 13, were newly identified as associated with canine fur shedding. [0125] The nucleotide sequences of cDNAs encoded by the canine genes from Canis lupus familiaris (MC2R1 (SEQ ID NO: 13), ANGPT1 (SEQ ID NO: 14), EIF3E (SEQ ID NO: 15), and PKHD1L1 (SEQ ID NO: 16) that were newly identified as associated with canine fur shedding are disclosed in Table 9 and the Sequence Listing incorporated herein. Table 9 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Fur Shedding through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein shedding, lists of genes within 2, 10, 20, 50, 100, 200, or 500 kb from each of the significant SNPs were generated. The only set of genes having enriched “biological process” GO terms were those found within 2 kB and 10 kB of those SNPs. See, FIG.9. Example 4 Identifying SNPs. Genes and Pathways that are Associated with Canine Individual Weight (Working) [0127] SNPs, genes, and pathways associated with canine individual weight were identified via GWAS methodologies employing multi-locus associations that accounted for kinship and/or population structure in combination with multiple testing correction. In some aspects of these GWAS methodologies, multiple testing correction was achieved via a multiple loci mixed linear model that incorporated multiple markers simultaneously as covariates to partially remove the confounding between testing markers and kinship. [0128] Table 10 discloses 18 significant single-nucleotide polymorphisms (SNPs) localized to chromosomes 1, 3, 4, 5, 7, 10, 11, 15, 18, 19, 30, 32, and 34, which were identified as associated with canine fur shedding. Table 10 Canine Individual Weight-associated SNPs that were identified via the GWAS Methodologies Disclosed Herein Table 10 Canine Individual Weight-associated SNPs that were identified via the GWAS Methodologies Disclosed Herein Table 10 Canine Individual Weight-associated SNPs that were identified via the GWAS Methodologies Disclosed Herein [0129] Single-nucleotide polymorphisms (SNPs) localized to chromosomes 1, 3, 4, 5, 7, 10, 11, 15, 18, 19, 30, 32, and 34 were identified as associated with canine individual weight. Each of those SNPs that were run through a gene mapping function and mapped to the underlying genes within 50 kb of those SNPs. The 37 Genes that were identified as associated with canine individual weight are summarized in Table 11. Table 11 Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 11 Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein [0130] The nucleotide sequences of cDNAs encoded by the canine genes from Canis lupus familiaris (XPOT (SEQ ID NO: 17), TBK1 (SEQ ID NO: 18), IGF1 (SEQ ID NO: 19), IGF2BP2 (SEQ ID NO: 20), GNAT3 (SEQ ID NO: 21), LCORL (SEQ ID NO: 22), CREBRF (SEQ ID NO: 23), ERGIC1 (SEQ ID NO: 24), MSRB3 (SEQ ID NO: 25), RASSF3 (SEQ ID NO: 26), ATP6V0E1 (SEQ ID NO: 27), PDE7B (SEQ ID NO: 28), WDR27 (SEQ ID NO: 29), DSE (SEQ ID NO: 30), TMC1 (SEQ ID NO: 31), POLN (SEQ ID NO: 32), NAT8L (SEQ ID NO: 33), LCORL (SEQ ID NO: 34), STC2 (SEQ ID NO: 35), ETS1 (SEQ ID NO: 36), SMAD2 (SEQ ID NO: 37), MLANA (SEQ ID NO: 38), KIAA2026 (SEQ ID NO: 39), UTP20 (SEQ ID NO: 40), ARL1 (SEQ ID NO: 41), SPIC (SEQ ID NO: 42), IGF1 (SEQ ID NO: 43), CRADD (SEQ ID NO: 44), MAGI2 (SEQ ID NO: 45), CD36 (SEQ ID NO: 46), LRP1B (SEQ ID NO: 47), RMDN3 (SEQ ID NO: 48), DNAJC17 (SEQ ID NO: 49), C30H15orf62 (SEQ ID NO: 50), ZFYVE19 (SEQ ID NO: 51), PPP1R14D (SEQ ID NO: 52), SPINT1 (SEQ ID NO: 53), GCHFR (SEQ ID NO: 54), CCSER1 (SEQ ID NO: 55), and IGF2BP2 (SEQ ID NO: 56) that were newly identified as associated with canine individual weight are disclosed in Table 12 and the Sequence Listing incorporated herein. Table 12 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 12 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 12 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 12 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein Table 12 Nucleotide Sequences of Canine cDNAs Encoded by Genes that were Associated with Canine Individual Weight through Analysis of SNPs identified via the GWAS Methodologies Disclosed Herein elbow dysplasia, lists of genes within 2 kB, 10 kB, and 50 kB from each of the significant SNPs were generated. No genes having enriched “biological process” GO terms were found within 2 kB, 10 kB, or 50 kB of those SNPs.