GENETIC MARKERS AND BIOSTATISTICAL METHODS AS APPROPRIATE TOOLS TO PRESERVE GENETIC RESOURCES

Abstract

The aim of presented study was to assess the most suitable way how to distinguish
different breeds based on molecular markers. One of the most difficult aspects of
quality assurance schemes is their reliability. The verification of fraud needs great
efforts in control strategies. The use of DNA markers has been shown to be a
useful tool for individual identification. It is necessary to use modern statistical
method based on data mining and supervised learning. Supervised pattern
recognition techniques use the information about the class membership of the
samples to a certain group (class or category) in order to classify new unknown
samples in one of the known classes on the basis of its pattern of measurements.
Large scale of supervised learning oriented method was used for traceability and
identification on individual level. A result of provided study shows the possibility
to classify unknown samples according to genetic data. Model is also useful for
classification on many logical levels as brand, region and many others. If we take
in the account only Slovak and Austrian Pinzgau cattle, based on SNP chip data, it
is not possible to separate them using Bayesian approach. Once we considered with
the admixture of breeds involved in the historical development as well as
inbreeding, selection signatures and migration, we were able to separate even
genetically similar breeds. It is possible distinguish between closely related
populations based on different markers. We just need to select the appropriate type
of analysis.