John Buckleton

An investigation of the rigor of interpretation rules for STRs derived from less than 100 pg of DNA

By increasing the PCR amplification regime to 34 cycles, we have demonstrated that it is possible routinely to analyse <100 pg DNA. The success rate was not improved (without impairing quality) by increasing cycle number further. Compared to amplification of 1 ng DNA at 28 cycles, it was shown that increased imbalance of heterozygotes occurred, along with an increase in the size (peak area) of stutters. The analysis of mixtures by peak area measurement becomes increasingly difficult as the sample size is reduced. Laboratory-based contamination cannot be completely avoided, even when analysis is carried out under stringent conditions of cleanliness. A set of guidelines that utilises duplication of results to interpret profiles originating from picogram levels of DNA is introduced. We demonstrate that the duplication guideline is robust by applying a statistical theory that models three key parameters - namely the incidence of allele drop-out, laboratory contamination and stutter. The advantage of the model is that the critical levels for each parameter can be calculated. This information may be used (for example) to determine levels of contamination that can be tolerated within the strategy employed. In addition we demonstrate that interpreting one banded loci, where allele dropout could have occurred, using LR=1/2f(a) was conservative provided that the band was low in peak area. Furthermore, we demonstrate that an apparent mis-match between crime-stain and a suspect DNA profile does not necessarily result in an exclusion. The method used is complex, yet can be converted into an expert system. We envisage this to be the next step.

Interpreting simple STR mixtures using allele peak areas

Although existing statistical models can interpret mixtures qualitatively based upon the alleles present, the use of automated sequencers opens the opportunity to take account of quantitative aspects embodied by the peak area. One step in understanding simple mixtures consisting of just two donors is to estimate the mixture ratio. This is relatively easy to do when four-allele mixtures are evident at a given locus. However, if the mixture consists of three or fewer alleles, the process it is not straightforward. We demonstrate that mixture estimates are consistent across all loci in a multiplex system. Once the mixture ratio is known, then the expected peak areas for any given combination of alleles can be estimated using a simple spreadsheet analysis.

The interpretation of single source and mixed DNA profiles

A method for interpreting autosomal mixed DNA profiles based on continuous modelling of peak heights is described. MCMC is applied with a model for allelic and stutter heights to produce a probability for the data given a specified genotype combination. The theory extends to handle any number of contributors and replicates, although practical implementation limits analyses to four contributors. The probability of the peak data given a genotype combination has proven to be a highly intuitive probability that may be assessed subjectively by experienced caseworkers. Whilst caseworkers will not assess the probabilities per se, they can broadly judge genotypes that fit the observed data well, and those that fit relatively less well. These probabilities are used when calculating a subsequent likelihood ratio. The method has been trialled on a number of mixed DNA profiles constructed from known contributors. The results have been assessed against a binary approach and also compared with the subjective judgement of an analyst.

Interpreting DNA Mixtures in Structured Populations

DNA profiles from multiple-contributor samples are interpreted by comparing the probabilities of the profiles under alternative propositions. The propositions may specify some known contributors to the sample and may also specify a number of unknown contributors. The probability of the alleles carried by the set of people, known or unknown, depends on the allelic frequencies and also upon any relationships among the people. Membership of the same subpopulation implies a relationship from a shared evolutionary history, and this effect has been incorporated into the probabilities. This acknowledgment of the effects of population structure requires account to be taken of all people in a subpopulation who are typed, whether or not they contributed to the sample.

Characterising stutter in forensic STR multiplexes

Stutter is an artefact seen when amplifying short tandem repeats and typically occurs at one repeat unit shorter in length than the parent allele. In forensic analysis, stutter complicates the analysis of DNA profiles from multiple contributors, known as mixed profiles, a common profile type. Consequently it is important to both understand and predict stutter behaviour in order to improve our understanding of the resolution and interpretation of these profiles. Whilst stutter is well recognised and documented, little information is available that identifies and quantifies what influences the formation of stutter. In this work we use a novel approach to examine this. We have used synthetic oligonucleotides comprising multiple repeat units to test; the influence of repeat number, the influence of repeat sequence and the impact of interruptions to the repeat sequence length. Using multiple replicates allows detailed statistical analysis. We have confirmed a linear relationship between stutter ratio and repeat number. We have shown that increased A-T content increases stutter ratio and that interruptions in repeating sequences decreased stutter ratios to levels similar to the longest uninterrupted repeat stretch. We also found that there was no relationship between stutter ratio and repeat number for a repeat unit with an A-T content of 1/4 and that half of the interrupted repeat sequences stuttered significantly less than their longest uninterrupted repeat stretches. We have applied the knowledge gained to examine specific features of the loci present in the AmpFlSTR(®) SGM Plus(®) multiplex kit used in our laboratory.

Developing allelic and stutter peak height models for a continuous method of DNA interpretation

Traditional forensic DNA interpretation methods are restricted as they are unable to deal completely with complex low level or mixed DNA profiles. This type of data has become more prevalent as DNA typing technologies become more sensitive. In addition they do not make full use of the information available in peak heights. Existing methods of interpretation are often described as binary which describes the fact that the probability of the evidence is assigned as 0 or 1 (hence binary) (see for example [1] at 7.3.3). These methods are being replaced by more advanced interpretation methods such as continuous models. In this paper we describe a series of models that can be used to calculate expected values for allele and stutter peak heights, and their ratio SR. This model could inform methods which implement a continuous method for the interpretation of DNA profiling data.

Towards understanding the effect of uncertainty in the number of contributors to DNA stains

DNA evidence recovered from a scene or collected in relation to a case is generally declared as a mixture when more than two alleles are observed at several loci. However, in principle, all DNA profiles may be considered to be potentially mixtures, even those that show not more than two alleles at any locus. When using a likelihood ratio approach to the interpretation of mixed DNA profiles it is necessary to postulate the number of potential contributors. However, this number is never known with certainty. The possibility of a, say three-person mixture, presenting four or fewer peaks at each locus of the CODIS set was explored by Paoletti et al. [D.R. Paoletti, T.E. Doom, C.M. Krane, M.L. Raymer, D.E. Krane, Empirical analysis of the STR profiles resulting from conceptual mixtures, J. Forensic Sci. 50 (2005) 1361-1366]. In this work we extend this analysis to consider the profiler plus and SGM plus multiplices. We begin the assessment of the risk associated with current practice in the calculation of LRs. We open the discussion of possible ways to surmount this ambiguity.

Evidence evaluation: A response to the court of appeal judgment in R v T

This is a discussion of a number of issues that arise from the recent judgment in R v T [1]. Although the judgment concerned with footwear evidence, more general remarks have implications for all disciplines within forensic science. Our concern is that the judgment will be interpreted as being in opposition to the principles of logical interpretation of evidence. We reiterate those principles and then discuss several extracts from the judgment that may be potentially harmful to the future of forensic science. A position statement with regard to evidence evaluation, signed by many forensic scientists, statisticians and lawyers, has appeared in this journal [2] and the present paper expands on the points made in that statement.

A discussion of the merits of random man not excluded and likelihood ratios

DNA mixture interpretation is undertaken either by calculating a LR or an exclusion probability (RMNE or its complement CPI). Debate exists as to which has the greater claim. The merits and drawbacks of the two approaches are discussed. We conclude that the two matters that appear to have real force are: (1) LRs are more difficult to present in court and (2) the RMNE statistic wastes information that should be utilised.

Examination of the variability in mixed DNA profile parameters for the Identifiler™ multiplex

The interpretation of mixed DNA profiles is often undertaken by determining to what extent possible genotype combinations may be eliminated from consideration. This requires an understanding of the variability in height or area for the two alleles of a heterozygote (heterozygote balance), and in the variability of mixture proportion or mixture ratio across loci. We present here empirical data to help assess the magnitude of this variability for Identifiler profiles. We find that heterozygote balance is affected by peak height as expected and that at heights above 267RFU the two peaks of a heterozygote demonstrates a peak height ratio between 0.6 and 1.66. For mixtures we introduce a concept, APH, the average peak heights of the active alleles. Above an APH of 110RFU mixture proportion demonstrated variation no more than 0.2 from the average across loci. Mixture ratio variability was affected by both the mixture ratio, M(r) per se and by the APH. The function (2APH/(1+M(r))) appears to be a reasonable predictor of the variability and approximates the expected peak height of the minor alleles. At (2APH/(1+M(r)))> or =300RFU the mixture ratio at a locus is expected to be within a factor of 2 of the average across loci.