Evaluating Mixture Solution™- rapid and non-MCMC probabilistic mixture analysis.

We compare DNA mixture analysis via DNAˑVIEW® Mixture Solution™ and the current combined probability of inclusion (CPI) method of the South African Police Service (SAPS). South Africa has a high incidence of property-related crimes and sexual offences and consequently a great deal of low-template (LT-DNA) forensic DNA mixture casework and a perpetual backlog. A range of casework and laboratory-prepared sexual assault mixtures with initial male DNA amounts varying from about 2 to 200 cells were analysed to evaluate the benefits of a continuous model program. Unfortunately CPI methods are nearly useless for LT-DNA cases because of dropout-common from a mixture contribution of fewer than 20 or 30 cells. We further argue that proposed CPI elaborations to circumvent dropout lack supporting research or even explanation. Mixture Solution models mixture data as continuous rather than binary, with a mathematically coherent ("probabilistic") model which incorporates dropout and other phenomena realistically. Much more information is thereby utilised resulting in applicability to more cases (7 or fewer contributor cells suffice), stronger evidence against a suspect who is a mixture contributor and stronger evidence to absolve a non-contributor. Mixture Solution incidentally provides information which, along with rfu data, allows estimating contributions in terms of number of cells, which is a useful perspective. The method of calculation is explained.

Allele frequency data of 15 autosomal STR loci in four major population groups of South Africa.

Allele frequency distributions for 15 tetrameric short tandem repeat (STR) loci were determined using the AmpFlSTR® Identifiler Plus™ PCR amplification kit. There was little evidence of departures from Hardy-Weinberg equilibrium or association of alleles of different loci in the population samples. The probability of identity values for the different populations range from 1/3.3 × 10(17) (White) to 1/1.88 × 10(18) (Coloured). The combined probability of paternal exclusion for the different population groups ranges from 0.9995858 (Coloured) to 0.9997874 (Indian).

Assessment of microsatellite and SNP markers for parentage assignment in ex situ African Penguin (Spheniscus demersus) populations.

Captive management of ex situ populations of endangered species is traditionally based on pedigree information derived from studbook data. However, molecular methods could provide a powerful set of complementary tools to verify studbook records and also contribute to improving the understanding of the genetic status of captive populations. Here, we compare the utility of single nucleotide polymorphisms (SNPs) and microsatellites (MS) and two analytical methods for assigning parentage in ten families of captive African penguins held in South African facilities. We found that SNPs performed better than microsatellites under both analytical frameworks, but a combination of all markers was most informative. A subset of combined SNP (n = 14) and MS loci (n = 10) provided robust assessments of parentage. Captive or supportive breeding programs will play an important role in future African penguin conservation efforts as a source of individuals for reintroduction. Cooperation among these captive facilities is essential to facilitate this process and improve management. This study provided us with a useful set of SNP and MS markers for parentage and relatedness testing among these captive populations. Further assessment of the utility of these markers over multiple (>3) generations and the incorporation of a larger variety of relationships among individuals (e.g., half-siblings or cousins) is strongly suggested.