Oast: central, CCS Central Coast: South (Santa Monica Mountains), PRE Peninsular
Oast: central, CCS Central Coast: South (Santa Monica Mountains), PRE Peninsular RangeEast, SAM Santa Ana Mountains. The plot is organized by grouping folks in order of their geographic area sampling supply. Proportional genetic assignment for every puma is represented by a vertical bar, most easily visualized for pumas that genetically assigned to a group different from most other people sampled in its region (for example 1 individual with more than 80 brown and 8 blue close to far left of group A). Pumas mostly from the Sierra Nevada Range and northern California are represented by group A (yellow), group B (brown) involves primarily Central Coast pumas and group C (blue) represents mainly southern California pumas (Santa Ana Mountains and eastern Peninsular Ranges). doi:0.37journal.pone.007985.gwere visualized with STRand version 2.three.69 [5]. Adverse controls (all reagents except DNA) and good controls (wellcharacterized puma DNA) have been included with each PCR run. Samples had been run in PCR at each locus at the very least twice to assure accuracy of genotype reads and minimize danger of nonamplifying alleles. For .90 samples, loci that had been heterozygous had been run at the least twice and homozygous loci were run a minimum of three occasions.Genetic diversityThe variety of alleles (Na), allelic richness (AR; incorporates correction for sample size), observed heterozygosity (Ho), expected heterozygosity (He), Shannon’s information index [6], and tests for deviations from HardyWeinberg equilibrium had been calculated employing software program GenAlEx version 6.five [7,8]. Shannon’s information and facts index supplies an alternative technique of quantifying genetic diversity and incorporates allele numbers and frequencies. Testing for deviations from expectations of linkage PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/23467991 equilibrium was conducted utilizing Genepop 4.2. [9], and we tested for the presence of null alleles using the program ML RELATE [20]. We assessed significance for calculations at alpha 0.05 and usedsequential Bonferroni corrections for a number of tests [2] in tests for HardyWeinberg and linkage equilibria. The average probability of identity (PID) was calculated two ways making use of GenAlEx: ) assuming random mating (PIDRM) with out close relatives in a NBI-56418 site population [22], and 2) assuming that siblings with equivalent genotypes occur within a population (PIDSIBS) [23]. Probability of identity could be the likelihood that two people will have the identical genetic profile (genotype) for the DNA markers employed. PIDSIBS is considered conservative given that it possibly conveys a higher likelihood; nevertheless, we recognized that siblings occurred in these populations.Assessing population structure and genetic isolationWe used a Bayesian genetic clustering algorithm (STRUCTURE version 2.three.four [24,25]) to identify the most likely variety of population groups (K; genetic clusters) and to probabilistically group people without the need of utilizing the recognized geographic location of sample collection. We utilized the population admixture model with a flat prior and assumed that allele frequencies had been correlated among populations, and ran 50,000 Markov chain Monte Carlo repetitions following a burnin period of 0,000 
repetitions. Initially,Figure four. Southern California puma population genetic structure. Bar Plot displaying benefits of STRUCTURE evaluation focused on genotypic information from 97 southern California pumas (the blue block from Figure 3). With removal in the powerful genetic signal from northern California and Central Coast samples (see Figure three), two distinct southern California grouping.