Small village populations in which there is a high amount of kinship can cause complications in cases of disaster victim identification. This problem was highlighted by the loss of life after Typhoon Morakot struck Taiwan where over 500 people from small isolated communities lost their lives. Most of the victims were buried by landslides in the remote mountainous areas of southern Taiwan. Only 146 pieces of human remains were recovered after searching for 4 months. Most of the human remains were received for examination as severely damaged fragments prevented possible identification by morphological features. DNA testing using the traditional duo parent/child or sibling screening by STR data opens the possibility of including not only the actual victim but also false positives. Variable likelihood ratios were obtained when comparing DNA types from human remains to those from potential relatives; however, with the DNA typing of numerous members of the same living family, multiple matches to potential families were avoided. Of the 146 samples obtained and collapsed to 130 victims, they were linked to 124 individuals resulting in their identification when compared to a pool of 588 potential relatives. Six of the human remains could not be linked to any living relative and remain unknown.

AimTo investigate the potential of false inclusion of a close genetic relative in paternity testing by using computer generated families.Methods10 000 computer-simulated families over three generations were generated based on genotypes using 15 short tandem repeat loci. These data were used in assessing the probability of inclusion or exclusion of paternity when the father is actually a sibling, grandparent, uncle, half sibling, cousin, or a random male. Further, we considered a duo case where the mother’s DNA type was not available and a trio case including the mother’s profile.ResultsThe data showed that the duo scenario had the highest and lowest false inclusion rates when considering a sibling (19.03 ± 0.77%) and a cousin (0.51 ± 0.14%) as the father, respectively; and the rate when considering a random male was much lower (0.04 ± 0.04%). The situation altered slightly with a trio case where the highest rate (0.56 ± 0.15%) occurred when a paternal uncle was considered as the father, and the lowest rate (0.03 ± 0.03%) occurred when a cousin was considered as the father. We also report on the distribution of the numbers for non-conformity (non-matching loci) where the father is a close genetic relative.ConclusionsThe results highlight the risk of false inclusion in parentage testing. These data provide a valuable reference when incorporating either a mutation in the father’s DNA type or if a close relative is included as being the father; particularly when there are varying numbers of non-matching loci.

AimTo use a virtually simulated population, generated from published allele frequencies based on 15 short tandem repeats (STR), to evaluate the efficacy of trio sibship testing and sibling assignment for forensic purposes.MethodsVirtual populations were generated using 15 STR loci to create a large number of related and unrelated genotypes (10 000 trio combinations). Using these virtual populations, the probability of related and unrelated profiles can be compared to determine the chance of inclusions of being siblings if they are true siblings and the chance of inclusion if they are unrelated. Two specific relationships were tested – two reference siblings were compared to a third true sibling (3S trio, sibling trio) and two reference siblings were compared to an unrelated individual (2S1U trio, non-sibling trio).ResultsWhen the likelihood ratio was greater than 1, 99.87% of siblings in the 3S trio population were considered as siblings (sensitivity); 99.88% of non-siblings in the 2S1U trio population were considered as non-siblings (specificity); 99.9% of both populations were identified correctly as siblings and non-siblings; and the accuracy of the test was 99.88%.ConclusionsThe high sensitivity and specificity figures when using two known siblings compared to a putative sibling are significantly greater than when using only one known relative. The data also support the use of increasing number of loci allowing for greater confidence in genetic identification. The system established in this study could be used as the model for evaluating and simulating the cases with multiple relatives.