Finding the genes for a genetic disorder without DNA

By Carol Beuchat PhD

Commercial DNA analysis has changed the way we breed dogs, giving us the ability to prevent disorders caused by recessive mutations with just a cheek swab. It has been less successful at addressing polygenic disorders. Identifying 12 genes "associated" with a health issue, with none identified as directly causal, poses a selection nightmare for breeders. What if your bitch has 4 of them and a potential mate has numerous others? What is the risk of producing puppies with problems? Can you discard all dogs with any of the genes, or even some of them, from the breeding program?

This is becoming a huge problems. Many breeds are wrestling with disorders that seem to be genetic because they run in breeds or families, but breeders can only guess at levels or risk involved in breeding a pair of dogs. Without some way to shed light on the underlying genetics of a probem, breeders have to weigh personal responsibility for health outcomes without useful information about risk. 

Several years ago, I wrote a blog post that described a way for breeders to deal with genetic disorders when nothing was known about the genes involved or mode or inheritance (Cool tricks with Kinship Coefficients, part 3: "How can I manage a disease without a DNA test?" ). In the past, the technique has been used to address several othewise intractable genetic problems in dogs, but it seems to be forgotton now that we look to DNA analysis to address genetic problems.

Recently, I was asked by some breeders of Yorkshire Terriers in Norway to see if I could help with the problem of liver shunts in this breed, and I decided to see if I could shed some light on the genetic basis of the problem using this technique.

The analysis uses a statistic computed from population genetics called the kinship coefficient, which quantifies the degree of relatedness between two dogs, assessed either from pedigree data or DNA. For a male and female, you determine the kinship coefficient for the pair, and that value is equal to the expected average coefficient of inbreeding in their puppies. This works because the kinship coefficient compares the genetic makeup of the sire and dam, then uses their genetic similarity (i.e., their relatedness) to estimate the degree of inbreeding if their genes were combined to produce puppies. In fact, this is how predicted litter COI is estimated in software that does test matings. 

So we have a statistic, the kinship coefficient, that allows us to assess the genetic similarity of two dogs. If you have a dog with a health issue (or any trait for that matter) that is suspected to be genetic, you would expect the dogs that are genetically similar to your dog would be more likely to carry the genes for the trait than dogs that were less similar. If you wanted to choose a mate that is less likely to carry the genes responsible for the health problem in your dog, you would look for individuals that are less similar genetically.

This seems logical enough, but how does this actually identify the dogs you could breed with that would have a lower risk of producing the disease? First, we need to identify as many dogs as we can that have been identified with the disorder, and we need the pedigree ancestry of these individuals. For a dog that has been diagnosed with the disorder, we know that it carries the risk genes that were inherited from its parents. This allows us to identify carriers of the risk genes, even though they are not affected and we don't know which specific genes are involved. 

Armed with the pedigree information for affected dogs in Norway, I performed a "cluster analysis" that identifies groups of closely related dogs using a "family tree" called a dendrogram, which is a visualization of the genetic reationships among groups of dogs. When I superimposed the information about affected Yorkies on the dendrogram, they all clustered in one group of relatives and there were none anywhere else among less related dogs.
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​What we have done is identify the dogs that carry the genes that produce liver shunt in Yorkies without knowing what those genes are. Breeding together two dogs from that same cluster of related dogs would increase the risk of producing puppies with liver shunt; breeders can reduce risk by simply avoiding those pairings. In fact, here is where the kinship coefficient between your bitch and a sire would tell you how similar they are genetically. You than reduce risk by finding a pairing with a lower kinship coefficient. 

This almost seems magical, but it's a very powerful technique. We have no easy way to breed for or against polygenic disorders or traits using DNA data, and staring at a pile of pedigrees doesn't tell a breeder much about risks in a quantitative way. But we know that the degree of genetic similarity of a pair of dogs will depend on how closely related they are. Just as we can use kinship coefficients to predict the average inbreeding of a litter of puppies, we can use them to evaluate risk of a genetic disorder.

The clever thing about this type of analysis is that it can be used for any trait with a genetic basis. It will work better when the heritability of the trait or disorder is high; that is, when most of the variation in the trait is due to genetics, and relatively less is a consequence of environmental (non-genetic) factors. In either case, it is a way of addressing genetic issues that are complex, involving both genes and environment. Most breeds have some issue that they are trying to deal with by selective breeding, but without any useful genetic information except knowing individuals that are actually affected. This is a way to address those problems.

We don't need DNA data to solve every genetic problem. Back before DNA analysis was available, breeders worked out ways to provide information about genetic risks knowing only about affected dogs and their relatives. Today, many breeds are struggling to manage health issues. Breeders should be aware that tools are available to help map a genetic landscape that seems to have no useful landmarks. 

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