Actions' Progress Action A.3 - Population estimation and monitoring of the genetic status of the bear sub-population in the project area

Action A.3 - Population estimation and monitoring of the genetic status of the bear sub-population in the project area

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Action A.3 was aiming in monitoring and evaluating the conservation status of the bear subpopulation in the area with the combination of traditional field surveys and the use of genetic methods of investigation. The whole of the brown bear distribution in the area was sampled using non-invasive techniques and laboratory analysis that focused on structure, diversity, and connectivity.

The methods used are briefly described as follows:

- DNA extraction: for this step specific protocols and isolation kits (Qiagen Mini Kit for hairs and blood samples, QiagenQIAmpDNAStoolMiniKit for stool samples) were used. For the hairs samples 1-15 roots/sample were cut under stereoscopic vision for DNA extraction from each root. Out of 174 samples, successful DNA extraction was achieved for 116 samples (76% success). For bear stools isolation process was more complicated and with lower success rate (22 out of 54 samples: 48% success). Regarding blood samples DNA isolation success rate was the highest (80%).

-DNA fingerprinting: 10 pairs of microsatellites molecular indicators enhanced with PCR (G10C, G10P, G1A, G10X, G1D, G10H, G10L, Mu50, Mu59, Mu26). In total 86 hair samples, 20 stools samples and 12 blood samples were used for further analyses.

- Gender definition: we used the method proposed by Pages et al. (2009), based on the two molecular indicators, one related to chromosome Υ (SRY gene) and another operating as witness during PCR reaction (ZF gene).

- Population size estimation:This was achieved by using software DROPOUT (McKelvey&Schwartz 2005) and CAPWIRE (Milleretal. 2005). Τhe latter is based on capture-mark-recapture method but differs from the classic methodology as the individuals can be captured several times during the same sample session. For the analysis statistical model TIRM which predicts the two categories of individuals according to their capture likelihood.

- Genetic variability: we used software GENEPOP 4.0 (Raymond&Rousset 1995) which calculates the different genetic variability parameters such as: observed (Ho) and expected (Hex) heterozygosis, inbreeding index (FIS) and deviation from Hardy-Weinberg balance. Moreover with the use of software Structure 2.2 (Pritchardetal. 2000) the existence of differentiated genetic groups was investigated. Finally software Genetixv. 4.05.2 (Belkhiretal. 1996–2004) was used to perform an FCA (factorialcorrespondenceanalysis) which yields a 3D graphic on the genetic relations between individuals from the same population.




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