Genetics of the domestic dog and the domestic cat have primarily focused on the elucidation of causative mutations for breed-specific diseases and phenotypic traits. Although several hundred mutations have been identified between the two species, a majority of the traits have had Mendelian forms of inheritance, including autosomal dominant, autosomal recessive, and X-linked inheritance. These "simple" traits can suffer from complicating factors, such as variable expression, delayed age of onset and incomplete penetrance. However, regardless of these complications, a vast majority of the mutations predict disease or phenotype with a very high degree of accuracy. These qualitative diseases and phenotypes tend to have a less significant influence from environmental influences and perturbances.

Unlike cats and dogs, genetics and genomics in agricultural species focuses on traits that are considered quantitative, whether in a cow, pig, chicken, fish, or shrimp. Quantitative trait loci (QTL) or economical trait loci (ETL), which are complex, imply interactions with the host and the environment that are required to explain the measured effects. Milk or meat production, including protein or fat content, energy usage, waste production, and wool quality are all traits that are controlled by a variety of genes with alleles that have large and small genetic effects that can be additive or counterproductive, similar or dissimilar in different breeds and populations. Good nutritional, reproductive, and general health can all interplay with the measured outcomes of the traits, hence must have interactions with the genes that produce the traits.

Whether for a household pet, such as a cat or dog, or a production animal, such as a cow or a chicken, the genetics and biology of infectious disease are a significant factor in healthcare, herd management, and productivity. Infectious disease susceptibility and resistance has even a higher level of complexity than other complex traits as besides the genetics and environment of the host, the genetics and environment of the pathogen must also be considered. The host's immune system must be considered and deciphered as well as the strain of the pathogen, considering each system's variables in a complex matrix of interactions. Deciphering the interactions is a slow and painstaking process as each aspect of exposure and infection needs to be deconvoluted and examined. Devising the perfect set of experiments that can peel away the layers of complexity is tedious and often unrealistic in the realm of the natural environment and conditions of the animal. One infectious disease that is under intense scrutiny in the domestic cat is feline enteric coronavirus infection that leads to the development of feline infectious peritonitis (FIP).

Feline enteric coronavirus (FECV) is a ubiquitous, worldwide, intestinal virus of cats (Pedersen et al. 1981a). The name feline coronavirus (FCoV) has been applied somewhat interchangeably to FECV. Technically, FCoV includes all strains (numerous), serotypes (types I and II), and biotypes (enteric or infectious peritonitis viruses) of the genus. The original FECV strain was designated FECV-UCD (Pedersen et al. 1981a), and another FECV-RM (Hickman et al. 1995), both of these strains belong to serotype I. Feline enteric coronavirus infection is usually unapparent or manifested by a transient gastroenteritis (Pedersen et al. 1981a); therefore, the importance of FECV as a primary intestinal pathogen is minimal. However, FECV commonly mutates in vivo and at least one mutant form (i.e., biotype) causes a highly fatal disease known as feline infectious peritonitis (FIP) (Poland et al. 1996; Vennema et al. 1998).

Feline infectious peritonitis mainly affects young cats from environments such as pedigreed catteries, shelters, and foster/rescue facilities. Disease prevalence is around 1–5% in these populations, but mortality among affected cats is virtually 100% once clinical signs appear. Feline infectious peritonitis virus (FIPV) differs from its strictly intestinal tropic FECV parent in its altered tropism for macrophages (Pedersen 1987; Stoddart and Scott 1989). This tropism allows the virus to become a systemic pathogen of macrophages, and the resultant disease involves a complex interaction between host cellular and humoral immunity and infected macrophages (Pedersen and Boyle 1980; Pedersen 1986). Feline infectious peritonitis virus infection manifests in two basic forms, termed wet (effusive, non-parenchymatous) or dry (non-effusive, parenchymatous). The form the disease takes is dependent on the type of immunity that develops. In addition to immune response, previous studies have implicated a number of intrinsic (host, virus) and extrinsic (stress, overcrowding) factors in the incidence of FIP in a given environment (Pedersen 2009). Foley and colleagues (1997) studied a number of risk factors for FIP in seven catteries and found that cat numbers (density) and husbandry procedures had no influence on FIP incidence, while age, high coronavirus antibody titers, and the proportion of cats shedding coronavirus were significantly associated with FIP risk. All of these risk factors are interrelated, because fecal coronavirus shedders are much more likely to have antibody titers > 1:100 and younger cats are more likely to shed FECV at higher levels and for longer periods (Pedersen et al. 2004; Pedersen et al. 2008). The stresses of placing young cats into shelters have also been shown to greatly increase the levels of FECV shedding (Pedersen et al. 2004). The severity of FECV exposure and age are of major importance (Foley et al. 1997). The stress of surgery, especially when performed at a young age, may increase susceptibility of cats to FIP development (Kass and Dent 1995). Co-infections with FeLV will greatly increase the incidence of FIP by interfering with FIP immunity; more than one-third of all FIP cases occurred in cats that were persistently infected with FeLV (Cotter et al. 1973; Pedersen et al. 1977). Feline immunodeficiency virus (FIV) can also compromise host immunity and increase FIP prevalence under experimental conditions (Poland et al. 1996). Evidence suggests genetics may be more important than previously assumed. Feline infectious peritonitis did not exist before the 1950s (Holzworth 1963), suggesting that cats may not have had time to genetically adapt, thus explaining why morbidity and mortality is so high in experimental FIPV infections. Pedigreed cats are more likely to develop FIP than random-bred cats (Robison et al. 1971; Rohrbach et al. 2001; Pesteanu-Somogyi et al. 2006; Worthing et al. 2012), and certain breeds are also more likely to succumb to FIP (Bell et al. 2006; Pesteanu-Somogyi et al. 2006; Worthing et al. 2012). One study of Persian catteries and pedigrees indicated that susceptibility to FIP was at least 50% heritable (Foley and Pedersen 1996). Resistance to FIP in Birman cats also appears to have a genetic component as determined by genome-wide association studies (GWAS) (Golovko et al. 2012).

Genetic studies have initiated for the analysis of FIP in domestic cats and specific cat breeds, such as the Birman. As described above, the strain of virus must be controlled, the time of exposure, the stresses during exposure and during early enteric pathogenesis. The immune response of the cat will likely dictate the form of FIP - wet versus dry - thus each of these forms must be an independent investigation. The genetic tools that are required to decipher complex interactions must be powerful and robust. Current DNA arrays for domestic cats have shown to be sufficiently powerful for the analysis of breeds and simple genetic traits. But more complex traits, or even simple traits in random-bred cats can be a daunting task for the current tools and resources. Genomic projects for the cat, such as projects to individually whole-genome sequence cats, will help drive the development of more complex DNA and expression arrays that will aid and abet the deciphering of the genetics of FIP and potentially identifying genes and alleles that may confer disease resistances or susceptibilities.

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