Review: domestic animal forensic genetics – biological evidence,genetic markers,analytical approaches and challenges

This review highlights the importance of domestic animal genetic evidence sources, genetic testing, markers and analytical approaches as well as the challenges this field is facing in view of the de facto ‘gold standard’ human DNA identification. Because of the genetic similarity between humans and domestic animals, genetic analysis of domestic animal hair, saliva, urine, blood and other biological material has generated vital investigative leads that have been admitted into a variety of court proceedings, including criminal and civil litigation. Information on validated short tandem repeat, single nucleotide polymorphism and mitochondrial DNA markers and public access to genetic databases for forensic DNA analysis is becoming readily available. Although the fundamental aspects of animal forensic genetic testing may be reliable and acceptable, animal forensic testing still lacks the standardized testing protocols that human genetic profiling requires, probably because of the absence of monetary support from government agencies and the difficulty in promoting cooperation among competing laboratories. Moreover, there is a lack in consensus about how to best present the results and expert opinion to comply with court standards and bear judicial scrutiny. This has been the single most persistent challenge ever since the earliest use of domestic animal forensic genetic testing in a criminal case in the mid‐1990s. Crime laboratory accreditation ensures that genetic test results have the courts’ confidence. Because accreditation requires significant commitments of effort, time and resources, the vast majority of animal forensic genetic laboratories are not accredited nor are their analysts certified forensic examiners. The relevance of domestic animal forensic genetics in the criminal justice system is undeniable. However, further improvements are needed in a wide range of supporting resources, including standardized quality assurance and control protocols for sample handling, evidence testing, statistical analysis and reporting that meet the rules of scientific acceptance, reliability and human forensic identification standards.     

An unconditional exact test for the Hardy-Weinberg equilibrium law: sample-space ordering using the Bayes factor

Much forensic inference based upon DNA evidence is made assuming that the Hardy-Weinberg equilibrium (HWE) is valid for the genetic loci being used. Several statistical tests to detect and measure deviation from HWE have been devised, each having advantages and limitations. The limitations become more obvious when testing for deviation within multiallelic DNA loci is attempted. Here we present an exact test for HWE in the biallelic case, based on the ratio of weighted likelihoods under the null and alternative hypotheses, the Bayes factor. This test does not depend on asymptotic results and minimizes a linear combination of type I and type II errors. By ordering the sample space using the Bayes factor, we also define a significance (evidence) index, P value, using the weighted likelihood under the null hypothesis. We compare it to the conditional exact test for the case of sample size n = 10. Using the idea under the method of chi(2) partition, the test is used sequentially to test equilibrium in the multiple allele case and then applied to two short tandem repeat loci, using a real Caucasian data bank, showing its usefulness.     

土壤微生物在法庭科学领域中的应用研究进展

土壤物证在法庭科学领域的应用由来已久,主要是基于其外观、颜色、元素组成、矿物学等理化特性及土壤夹杂物等的比对检验。近年来,随着高通量测序技术的发展,法医土壤微生物检验不再完全依赖于传统培养技术,而是直接挖掘分析土壤中的全部微生物DNA信息,并将这些信息应用于法庭科学领域内的样本比对、土壤物证区域环境推断和溯源研究等,从而凸显出土壤微生物物证在案件侦查和法庭诉讼方面的巨大价值和应用潜力。本文通过综述国内外有关法医土壤微生物研究的最新进展,指出了土壤微生物多样性检验在法庭科学领域的应用潜力,分析了法医土壤微生物群落多样性的影响因素,最后探讨了法医土壤微生物研究中存在的问题和未来的发展方向。     

人D6S1043-1型STR质粒DNA标准物质的研制

短串联重复序列（short tandem repeat，STR）是存在于人类基因组中的一类具有长度多态性的DNA序列，由含2~6个碱基对的重复单位串联构成。DNA STR分型检验是当前法庭科学进行个体识别和亲缘鉴定的主要依据。STR分型标准物质是DNA STR检验量值溯源的基础和关键物质，对其进行研究将极大推动我国法庭科学DNA STR检验的标准化进程。以STR基因座D6S1043为例，介绍人类基因组中STR序列的质粒DNA标准物质的制备过程。首先，合成包含13个重复单元（\[ATCT\]13）的D6S1043序列（定义为D6S1043-1）并将其与pUC57载体连接构建重组质粒，制备质粒溶液。其次，通过酶切鉴定、Sanger测序、多种STR分型试剂盒的分型鉴定等方法检验DNA序列的准确性。再次，采用微滴式数字PCR方法（droplet digital PCR，ddPCR）检测质粒浓度，评估质粒溶液的均匀性和稳定性。最后，由8家实验室协作，测定浓度标准值，综合分析均匀性检验、稳定性检验、定值过程等引入的不确定度，得到总不确定度；由6家实验室协作，测定D6S1043-1的分型值。结果表明：该标准物质的均匀性、稳定性良好，在-20 ℃可保存6个月，在4 ℃可保存14 d；核酸拷贝数为（7.7±1.2）×103 copies·μL-1；在D6S1043基因座上的分型值为13。人D6S1043-1型STR质粒DNA标准物质 \[编号：GBW（E）091072\] 是我国法庭科学DNA检验领域首批有证标准物质之一，其研制过程为其他STR基因座的质粒DNA标准物质的研制提供了一定的借鉴。     

Reliability of DNA cytometric S-phase analysis in surgical biopsies: assessment of systematic and sampling errors and comparison between results obtained by image and flow cytometry

Three major parameters in DNA histograms that contribute to the reliability of S-phase analysis were evaluated. These parameters are (1) the extent of background in relation to the amount of S-phase cells (and the validity of its subtraction), (2) the size of the "free" S-phase range (S(free)), and (3) the sampling error of cell counting. Tests in histograms obtained from surgical biopsies by flow cytometry (FCM) showed that the background subtraction is reliable if the found S-phase fraction is higher than the fraction of background events in the histogram range of the cell population. The size of S(free) was determined in computer-generated test histograms as a function of variables such as the coefficient of variation (CV) and the DNA index (DI). To calculate the sampling error of cell counting above background and in S(free), a model was developed that was validated by experimental data. This error can serve as an indicator of the uncertainty in S-phase analysis. The poor correlation found between %S values measured by image cytometry (ICM) and FCM in surgical biopsies was assigned to high uncertainty by low cell numbers in ICM histograms. A method is proposed to estimate quantitatively the reliability of S-phase analysis that can facilitate the interpretation of results.     

Forensic fictions: Science,television production,and modern storytelling

This essay uses interviews with television creators, writers, and producers to examine how media practitioners utilise, negotiate and transform forensic science in the production of televisual stories including the creation of unique visuals, character exploration, narrative progression, plot complication, thematic development, and adding a sense of authenticity. Television as a medium has its own structures and conventions, including adherence to a show’s franchise, which put constraints on how stories are told. I demonstrate how television writers find forensic science to be an ideal tool in navigating television’s narrative constraints by using forensics to create conflicts, new obstacles, potential solutions, and final solutions in their stories. I show how television writers utilise forensic science to provide the scientific certainty their characters require to catch the criminal, but also how uncertainty is introduced in a story through the interpretation of the forensics by the show’s characters. I also argue that televisual storytellers maintain a flexible notion of scientific realism based on the notion of possibility that puts them at odds with scientists who take a more demanding conception of scientific accuracy based on the concept of probability.     

Adaptive dose-finding: Proof of concept with type I error control

We consider an adaptive dose‐finding study with two stages. The doses for the second stage will be chosen based on the first stage results. Instead of considering pairwise comparisons with placebo, we apply one test to show an upward trend across doses. This is a possibility according to the ICH‐guideline for dose‐finding studies (ICH‐E4). In this article, we are interested in trend tests based on a single contrast or on the maximum of multiple contrasts. We are interested in flexibly choosing the Stage 2 doses including the possibility to add doses. If certain requirements for the interim decision rules are fulfilled, the final trend test that ignores the adaptive nature of the trial (naïve test) can control the type I error. However, for the more common case that these requirements are not fulfilled, we need to take the adaptivity into account and discuss a method for type I error control. We apply the general conditional error approach to adaptive dose‐finding and discuss special issues appearing in this application. We call the test based on this approach Adaptive Multiple Contrast Test. For an example, we illustrate the theory discussed before and compare the performance of several tests for the adaptive design in a simulation study.     

Dangers in testing statistical hypotheses

Most experiments are intended for the estimation of the size of effects rather than for the testing of a hypothesis of whether or not an effect occurs. Hypothesis testing is often inapplicable, is over-used and is likely to lead to misinterpretations of results. The two types of error possible in hypothesis testing are discussed. Whereas Type I error is usually examined as a matter of course, Type II error is almost always ignored. Investigations in which zero differences are important should recognise the possibility of Type II error in their interpretation. A nonsignificant result should not be interpreted as evidence of a lack of effect. Statistical significance is not synonymous with economic or scientific importance. The importance of choosing the most appropriate design is emphasised and some suggestions are made as to how important sources of error can be avoided.     

High-resolution melt analysis of DNA methylation to discriminate semen in biological stains

The goal of this study was to develop a method for the detection of semen in biological stains using high-resolution melt (HRM) analysis and DNA methylation. To perform this task, we used an epigenetic locus that targets a tissue-specific differentially methylated region for semen. This specific locus, ZC3H12D, contains methylated CpG sites that are hypomethylated in semen and hypermethylated in blood and saliva. Using this procedure, DNA from forensic stains can be isolated, processed using bisulfite-modified polymerase chain reaction (PCR), and detected by real-time PCR with HRM capability. The method described in this article is robust; we were able to obtain results from samples with as little as 1 ng of genomic DNA. Samples inhibited by humic acid still produced reliable results. Furthermore, the procedure is specific and will not amplify non-bisulfite-modified DNA. Because this process can be performed using real-time PCR and is quantitative, it fits nicely within the workflow of current forensic DNA laboratories. As a result, it should prove to be a useful technique for processing trace evidence samples for serological analysis.     

The effect of relatedness on likelihood ratios and the use of conservative estimates

DNA profiling can be used to identify criminals through their DNA matching that left at the scene of a crime. The strength of the evidence supplied by a match in DNA profiles is given by the likelihood ratio. This, in turn, depends upon the probability that a match would be produced if the suspect is innocent. This probability could be strongly affected by the possibility of relatedness between the suspect and the true source of the scene-of-crime DNA profile. Methods are shown that allow for the possibility of such relatedness, arising either through population substructure or through a family relationship. Uncertainties about the likelihood ratio have been taken as grounds for the use of very conservative estimates of this quantity. The use of such conservative estimates can be shown to be neither necessary nor harmless.Editor's commentsThe author makes a good case for the use of likelihood ratios in presenting evidence. The author cites Nichols and Balding (1991) for the match probability involvingF _ST , and readers will also need to consult Balding and Nichols (1994 and this volume) and Weir (1994). In light of current concern over laboratory errors or fraud, the author's comment that Undetected and unsuspected human error or mischief is potentially a problem in almost all criminal cases, yet no convictions could follow if this possibility was consistently deemed to lead to reasonable doubt is well taken.     

At the Edge of Safety: Moral Experimentation in the Case of Family Therapy

“At the Edge of Safety” argues for thinking of structural family therapy as a “moral laboratory.” Borrowing a trope from Cheryl Mattingly’s recent book Moral Laboratories, the article reconsiders a therapeutic style that was once controversial by analyzing personal stories of supervision—i.e. professional training—in light of Mattingly’s suggestion that a social space in which people conduct experiments on themselves and their lives may be considered a moral laboratory. Family therapy is especially good to think with, because it is simultaneously a real and a metaphorical laboratory, physically lab-like in its use of visual technologies, yet moral in the way it puts the possibility for situational change in the hands of human actors. The technological apparatus stages evidence for sub-visible, interpersonal dynamics, while the provocative quality of not only therapeutic actions, but also of supervision, points to an ethos of experimentation. Stories of supervision reveal how personal of an experience being supervised can be. Trainees are pushed to become something otherwise, in learning to “expand” their styles. Sometimes the push is just right. Sometimes it goes too far. Whatever the case may be, the stories analyzed speak to anthropological questions concerning the uncertainty of human action and the many ways people can unknowingly injure one another with small hurts.     

Calculating and Describing Uncertainty in Risk Assessment: The Bayesian Approach

Quantification of uncertainty associated with risk estimates is an important part of risk assessment. In recent years, use of second-order distributions, and two-dimensional simulations have been suggested for quantifying both variability and uncertainty. These approaches are better interpreted within the Bayesian framework. To help practitioners better use such methods and interpret the results, in this article, we describe propagation and interpretation of uncertainty in the Bayesian paradigm. We consider both the estimation problem where some summary measures of the risk distribution (e.g., mean, variance, or selected percentiles) are to be estimated, and the prediction problem, where the risk values for some specific individuals are to be predicted. We discuss some connections and differences between uncertainties in estimation and prediction problems, and present an interpretation of a decomposition of total variability/uncertainty into variability and uncertainty in terms of expected squared error of prediction and its reduction from perfect information. We also discuss the role of Monte Carlo methods in characterizing uncertainty. We explain the basic ideas using a simple example, and demonstrate Monte Carlo calculations using another example from the literature.     

And the helix may set you free

The first application of DNA forensics evidence was carried out by Dr. Alec Jefferies in 1983, in a British court case that sought to identify the relationship between an emigrant and her son. Since then, genotyping technology (also known as DNA fingerprinting and genetic profiling) has been developed and applied to identifying individuals for a wide variety of purposes including exonerating convicts. Faulty forensic evidence is a common cause of wrongful convictions. And once convicted, access to the forensic evidence remains a clear barrier to possible exoneration. In fact, it is DNA exoneration that is driving state legislators to address some of the apparent legislative flaws that govern forensic evidence testing in the U.S.     

A procedure for the statistical evaluation of Ames Salmonella assay results. Comparison of results among 4 laboratories

Ames Salmonella test data collected in our laboratory and 3 National Cancer Institute contract laboratories were analyzed to study the distribution of experimental errors associated with the test. It is shown that the Poisson distribution is not appropriate, and that the power transformation model Y = (revertants/plate)lambda, with lambda = 0.2 as estimated by the methods of Box and Cox, produced a measurement scale on which the experimental errors could be adequately described by a normal (Gaussian) distribution with a constant variance. The modeling procedure enables one to properly use analysis of variance, regression analysis, and Student's t test to analyze Ames Salmonella test results, and well-known statistical quality control procedures to monitor laboratory performance. The method detects weak mutagenic activity and measures the amount and uncertainty of the increase in revertants/plate. The development of the power transformation model is discussed and examples of its use in the interpretation of Ames Salmonella assay results are included.     

Identification of individuals by analysis of biallelic DNA markers, using PCR and solid-phase minisequencing.

We have developed a new method for forensic identification of individuals, in which a panel of biallelic DNA markers are amplified by the PCR, and the variable nucleotides are detected in the amplified DNA fragments by the solid-phase minisequencing method. A panel of 12 common polymorphic nucleotides located on different chromosomes with reported allele frequencies close to .5 were chosen for the test. The allele frequencies for most of the markers were found to be similar in the Finnish and other Caucasian populations. We also introduce a novel approach for rapid determination of the population frequencies of biallelic markers. By this approach we were able to determine the allele frequencies of the markers in the Finnish population, by quantitative analysis of three pooled DNA samples representing 3,000 individuals. The power of discrimination and exclusion of the solid-phase minisequencing typing test with 12 markers was similar to that of three VNTR markers that are routinely used in forensic analyses at our institute. The solid-phase minisequencing method was successfully applied to type paternity and forensic case samples. We also show that the quantitative nature of our method allows typing of mixed samples.     

Multiple testing in fetal gender determination from maternal blood by polymerase chain reaction

Fetal male DNA can be identified in maternal blood by polymerase chain reaction (PCR) amplification of Y-specific sequences. This technology has not reached a satisfactory accuracy and reproducibility in fetal gender determination because of the very low concentration of fetal cells. Our purpose was to evaluate the possibility of improving the reliability of this test by setting up a repeated amplification system. We amplified, by nested PCR of the Y-specific sequence DYS14, 137 DNA samples extracted from maternal peripheral blood (93 from male-bearing and 44 from female-bearing pregnancies ranging from the 6th to the 36th gestational week). Each maternal DNA sample was tested doubly, in two different PCR sessions, with a total of four amplifications. We obtained discordant results in the four amplifications in 82/137 (60%) samples. The best interpretation of these discordant results was obtained by applying a positivity cutoff of at least two positive amplifications for considering a DNA sample as belonging to a male-bearing pregnancy. We obtained a sensitivity of 83%, a specificity of 93%, a positive predictive value of 96% and a negative predictive value of 72% in fetal male gender diagnosis. By applying this quadruple testing system, we significantly improved PCR accuracy and predictive values compared with single and double testing of the same samples. We conclude that, for future investigations of fetal DNA retrieved from maternal blood, the application of a quadruple testing system is better than the single PCR test. Received: 18 August 1997 / Accepted: 12 January 1998     

Hair analysis for drugs of abuse. Plausibility of interpretation

Over more than 20 years hair analysis for drugs has been gaining increasing attention and recognition in various toxicological fields as preemployment and employment screening, forensic sciences, doping control of banned substances, clinical diagnostics in health problems. Hair analysis for drugs can expand the toxicological examination of conventional materials and thus contribute with additional important information to the complex evaluation of a certain case. Hair is a unique material for the retrospective investigation of chronic drug consumption, intentional or unintentional chronic poisoning in criminal cases, gestational drug exposure or environmental exposure to pollutants and adulterants and with specific ultrasensitive procedures allow to demonstrate even a previous single dose administration in a very low amount. Assuming the ideal hair steady and uniform growth, segmental hair analysis can provide the information about the time course of the substance use or exposure. However, the physiological background of hair growth, mechanisms of drug incorporation are not simple, not yet understood in full details and need not be evaluated exactly in all cases. The hair sampling, storage, sample preparation, analytical performance themselves are also very important for final results. Different laboratory attitudes can produce different results. The full information on circumstances of the case examined must be taken into account during interpretation. The pitfalls in hair analysis should be known and avoided to assure the responsible and correct interpretation of laboratory results adequate to an individual case.     

Forensic DNA and bioinformatics

The field of forensic science is increasingly based on biomolecular data and many European countries are establishing forensic databases to store DNA profiles of crime scenes of known offenders and apply DNA testing. The field is boosted by statistical and technological advances such as DNA microarray sequencing, TFT biosensors, machine learning algorithms, in particular Bayesian networks, which provide an effective way of evidence organization and inference. The aim of this article is to discuss the state of art potentialities of bioinformatics in forensic DNA science. We also discuss how bioinformatics will address issues related to privacy rights such as those raised from large scale integration of crime, public health and population genetic susceptibility-to-diseases databases.     

Prioritizing regionalization to enhance interpretation in consequential life cycle assessment: application to alternative transportation scenarios using partial equilibrium economic modeling

Purpose

Consequential life cycle assessment (C-LCA) aims to assess the environmental consequences of a decision. It differs from traditional LCA because its inventory includes all the processes affected by the decision which are identified by accounting for causal links (physical, economic, etc.). However, C-LCA results could be quite uncertain which makes the interpretation phase harder. Therefore, strategies to assess and reduce uncertainty in C-LCA are needed. Part of uncertainty in C-LCA is due to spatial variability that can be reduced using regionalization. However, regionalization can be complex and time-consuming if straightforwardly applied to an entire LCA model.

Methods

The main purpose of this article is to prioritize regionalization efforts to enhance interpretation in C-LCA by assessing the spatial uncertainty of a case study building on a partial equilibrium economic model. Three specific objectives are derived: (1) perform a C-LCA case study of alternative transportation scenarios to investigate the benefits of implementing a public policy for energy transition in France by 2050 with an uncertainty analysis to explore the strength of our conclusions, (2) perform global sensitivity analyses to identify and quantify the main sources of spatial uncertainty between foreground inventory model from partial equilibrium economic modeling, background inventory model and characterization factors, (3) propose a strategy to reduce the spatial uncertainty for our C-LCA case study by prioritizing regionalization.

Results and discussion

Results show that the implementation of alternative transport scenarios in compliance with public policy for the energy transition in France is beneficial for some impact categories (ICs) (global warming, marine acidification, marine eutrophication, terrestrial acidification, thermally polluted water, photochemical oxidant formation, and particulate matter formation), with a confidence level of 95%. For other ICs, uncertainty reduction is required to determine conclusions with a similar level of confidence. Input variables with spatial variability from the partial equilibrium economic model are significant contributors to the C-LCA spatial uncertainty and should be prioritized for spatial uncertainty reduction. In addition, characterization factors are significant contributors to the spatial uncertainty results for all regionalized ICs (except land occupation IC).

Conclusions

Ways to reduce the spatial uncertainty from economic modeling should be explored. Uncertainty reduction to enhance the interpretation phase and the decision-making should be prioritized depending on the goal and scope of the LCA study. In addition, using regionalized CFs in C-LCA seems to be relevant, and C-LCA calculation tools should be adapted accordingly.