Paternity Testing Commission of the International Society of Forensic Genetics: recommendations on genetic investigations in paternity cases.

The International Society for Forensic Genetics (ISFG) has established a Paternity Testing Commission (PTC) with the purpose of formulating international recommendations concerning genetic investigations in paternity testing. The PTC recommends that paternity testing be performed in accordance with the ISO 17025 standards. The ISO 17025 standards are general standards for testing laboratories and the PTC offers explanations and recommendations concerning selected areas of special importance to paternity testing.

'Stochastic' effects at balanced mixtures: a calibration study.

DNA mixtures are challenging not only at low template DNA level but also at highly balanced quantitative ratio. In this latter case, interpretation may be complicated by the joint action of combinatorial uncertainty and stochastic effects of the PCR. We explore this particular and so far little noticed aspect of mixture interpretation by first providing a complete quantitative combinatorial analysis of the two-person mixture model (2PM) at highly balanced ratio of contributors, and then by carrying out a calibration study of the 2PM model on good quality experimental mixtures. The calibration tests provided the evidence for the existence of irregular distribution of peak heights, that can misguide the correct genotype assignment at high template ratios too. Repeating the experiment, performing Bayesian analysis to the whole evidence and developing a careful joint prediction of all plausible genotype datasets is highly mandatory in these cases, prior to set evidentiary LRs and use them in court.

Joint Bayesian analysis of forensic mixtures.

Evaluation of series of PCR experiments referring to the same evidence is not infrequent in a forensic casework. This situation is met when 'series of results in mixture' (EPGs produced by reiterating PCR experiments over the same DNA mixture extract) have to be interpreted or when 'potentially related traces' (mixtures that can have contributors in common) require a combined interpretation. In these cases, there can be uncertainty on the genotype assignment, since: (a) more than one genotype combination fall under the same peak profile; (b) PCR preferential amplification alters pre-PCR allelic proportions; (c) other, more unpredictable technical problems (dropouts/dropins, etc.) take place. The uncertainty in the genotype assignment is in most cases addressed by empirical methods (selection of just one particular profile; extraction of consensual or composite profiles) that disregard part of the evidence. Genotype assignment should conversely take advantage from a joint Bayesian analysis (JBA) of all STRs peak areas generated at each experiment. This is the typical case of Bayesian analysis in which adoption of object-oriented Bayesian networks (OOBNs) could be highly helpful. Starting from experimentally designed mixtures, we created typical examples of 'series of results in mixture' of 'potentially related traces'. JBA was some administered to the whole peak area evidence, by specifically tailored OOBNs models, which enabled genotype assignment reflecting all the available evidence. Examples of a residual ambiguity in the genotype assignment came to light at assumed genotypes with partially overlapping alleles (for example: AB+AC→ABC). In the 'series of results in mixture', this uncertainty was in part refractory to the joint evaluation. Ambiguity was conversely dissipated at the 'potentially related' trace example, where the ABC allelic scheme at the first trace was interpreted together with other unambiguous combinations (ABCD; AB) at the related trace. We emphasize the need to carry out extensive, blind sensitivity tests specifically addressing the residual ambiguity that arises from overlapping results mixed at various quantitative ratios.

Phylogenetic evidence for multiple independent duplication events at the DYS19 locus.

Duplication events at Y chromosome STR loci have been repeatedly described in human populations. DYS19 is probably the best known example and it exhibits duplicate state in individuals from all continents. Despite the large amount of available data, evolutionary relationship between DYS19 duplication-bearing chromosomes has not been so far investigated. We address the genealogical correlation among such chromosomes by analysing newly identified DYS19 duplicated Y chromosomes by SNP genotyping and microsatellite-based network analysis. SNP and network analysis show that DYS19 duplicated Y chromosomes associate with different Y chromosome lineages. These results indicate that DYS19 duplication occurred more than once during human evolution.

ISFG: Recommendations on biostatistics in paternity testing.

The Paternity Testing Commission (PTC) of the International Society for Forensic Genetics has taken up the task of establishing the biostatistical recommendations in accordance with the ISO 17025 standards and a previous set of ISFG recommendations specific to the genetic investigations in paternity cases. In the initial set, the PTC recommended that biostatistical evaluations of paternity are based on a likelihood ratio principle - yielding the paternity index, PI. Here, we have made five supplementary biostatistical recommendations. The first recommendation clarifies and defines basic concepts of genetic hypotheses and calculation concerns needed to produce valid PIs. The second and third recommendations address issues associated with population genetics (allele probabilities, Y-chromosome markers, mtDNA, and population substructuring) and special circumstances (deficiency/reconstruction and immigration cases), respectively. The fourth recommendation considers strategies regarding genetic evidence against paternity. The fifth recommendation covers necessary documentation, reporting details and assumptions underlying calculations. The PTC strongly suggests that these recommendations should be adopted by all laboratories involved in paternity testing as the basis for their biostatistical analysis.