Low template DNA analysis: Further developments supporting its use in the criminal justice process
✍ Scribed by M.J. Greenhalgh
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 53 KB
- Volume
- 50
- Category
- Article
- ISSN
- 1355-0306
No coin nor oath required. For personal study only.
✦ Synopsis
improvements to the separation platform and detection instrumentation. If the starting DNA amount is lowered, a number of interpretational challenges follow. It is on these that this presentation will focus. DNA profiles produced from crime samples are affected by a number of wellrecognised and characterised artefacts resulting from the amplification and detection systems used. One phenomenon is stutter. This is caused by slippage of the TAQ polymerase during PCR. Typically this is evident as a small peak one-repeat unit below the larger 'parent' peak. Although generally small, it is known that the proportion of the stutter peak relative to the parent peak increases as the amount of starting DNA decreases. Ultimately, this causes interpretational challenges as it may be unclear whether a peak in a stutter position is an artefact or is truly an allele. Furthermore, during amplification of a heterozygous locus, the sister alleles amplify asymmetrically (often referred to as heterozygote imbalance). As the starting DNA amount is progressively reduced, heterozygote imbalance becomes increasingly variable due to stochastic effects leading ultimately to the failure to detect one of the pair of alleles ('allelic dropout') or often both alleles ('locus dropout'). Dropout poses a significant challenge in assigning weight to DNA evidence. Specifically, how does one assess the value of a purported match if a locus in a crime sample lacks one allele seen in the corresponding locus in a reference sample? In this talk we present a probabilistic model for assigning weight to DNA evidence where profiles may be affected by stutter and dropout. The model uses continuous probability distributions estimated from real data generated in our laboratory. The probability distributions allow us to model stutter height and peak imbalance. They dispense with the need to 'edit out a peak' as being a stutter and can deal with peak imbalance even in those extreme situations where dropout has to be asserted in order to be considered a 'match'.