Over the course of the last year I have been assembling information on the Swedish Vallhunds. The starting point was my own dog with a five-generation pedigree. At first the state of the breed seems to be relatively positive with low Co-efficient of Inbreeding (COI) once I have plugged in data, provided through SVPedigrees maintained by Sharon Donaldson in Australia; using Microsoft Excel and OpenOffice Spreadsheet at first then later BreedMate PedX. However, there were many holes in his pedigree.
A much more comprehensive dataset was extracted from Worldwide Swedish Vallhunds – Västgötaspets Pedigree
Database once kept by the now-deceased Leone Darling. It is rather a shame due to the death of a predominant breed historian, the domain will one day be taken down once it expires since the information is much more complete with far fewer errors. Using the dataset from Ms. Darling provided a much clearer picture.
When Christopher Landauer revealed one must go back to the founders to get a more reliable calibration of a dog’s COI, a graph of why it is not enough to look at the COI(3) and COI(5) was produced. With Riley, we will take a look at the COI(29).
Distressed by the relatively high COI, more information on the founders and popular sires and brood bitches was needed. To understand why such a high COI was procured, we must first understand what a pedigree collapse is. However the entire tree is relatively compact and there are a few noticeable collapses at a glance. The good news is they are not frequent. The bad news is not all the known founders are included in his complete pedigree. This hints the possibility several lines died out.
When inquiring numerous breeders about this issue with Riley, it was learned he is very typical of the breed. In fact, he is a relatively accurate sample of the Swedish Vallhund population.
So what happened? The modern population of Swedish Vallhunds, in which there is approximately 500 registrations world-wide every year, once had a more diverse ancestral base. A great number of potentials were rejected due to poor understanding of recessives and lack of knowledge of concepts essential to population genetics and quantitative genetics such as allele frequency and polygenes when the breeding program first initiated even though the rejects had obvious influences or characteristics. Ontop of the inability to recognize suitors, many of the progeny were sold unregistered and only the ones who were seen as ideal for breeding were registered for many decades after the founding of the Swedish Vallhunds. In addition, there were a few kennels between 1960s and 1970s producing surpluses of puppies which coincided with the extinction of several dam-lines and a a couple of sire-lines in the 1970s and 1980s. The bleeding of the breed slowed down when the Swedish Kennelklubben mandated entire litters must be registered in the 1980s, and a rule was passed in the 1990s stating a sire cannot contribute more than 5% of the existing gene-pool. As the result, conductor was able to slow down the train to hell.
However using pedigree software are quite limiting and they don’t tell us a great deal of information. There are quite a few of them out there. One of the easiest software to utilize, often used in population genetics, ecology and conservation biology for visualization, although the original purpose of the software was for discovering new relations between proteins in biochemstry and genomic laboratories, is an open-source network analysis program such as: Cyptoscope, Gephi, Pajek, BioLayout Express3D. There are plenty of software floating around on the Internet which regurge useful information.
In the next post, an illustration using a node-mapping software will be provided and explained. We will walk through as we add more information to the dataset and change how it is processed, different interpretations arise. We will also explore why in a competitive world where everyone is more concerned with their self-image, a pedigree record is rather limiting. A pedigree is a tool which only becomes more useful as more hard data is added.











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