Protecting privacy of individuals is critical for forensic genetics. In a kinship/identity testing, related DNA profiles between user's query and the DNA database need to be extracted. However, unrelated profiles cannot be revealed to each other. The challenge is today's DNA database usually contains millions of DNA profiles, which is too big to perform privacy-preserving query with current cryptosystem directly. In this thesis, we propose a scalable system to support privacy-preserving query in DNA Database. A two-phase strategy is designed: the first is a Short Tandem Repeat index tree for quick fetching candidate profiles from disk. It groups loci of DNA profiles by matching probability, so as to reduce I/O cost required to find a particular profile. The second is an Elliptic Curve Cryptosystem based privacy-preserving matching engine, which performs match between candidates and user's sample. In particular, a privacy-preserving DNA profile matching algorithm is designed, which achieves O(n) computing time and communication cost. Experimental results show that our system performs well at query latency, query hit rate, and communication cost. For a database of one billion profiles, it takes 80 seconds to return results to the user.

Indiana University-Purdue University Indianapolis (IUPUI) / In the forensic science community, there is an immense need for tools to help assist investigations where conventional DNA profiling methods have been non-informative. Forensic DNA Phenotyping (FDP) aims to bridge that gap and aid investigations by providing physical appearance information when other investigative methods have been exhausted. To create a “biological eye witness”, it becomes necessary to constantly improve these methods in order to develop a complete and accurate image of the individual who left the sample. To add to our previous prediction systems IrisPlex and HIrisPlex, we have developed the HIrisPlex-S system for the all-in-one combined prediction of eye, hair, and skin color from DNA. The skin color prediction model uses 36 variants that were recently proposed for the accurate prediction of categorical skin color on a global scale, and the system is completed by the developmental validation of a 17-plex capillary electrophoresis (CE) genotyping assay that is run in conjunction with the HIrisPlex assay to generate these genotypes. The predicted skin color output includes Very Pale, Pale, Intermediate, Dark and Dark-to-Black categories in addition to categorical eye (Blue, Intermediate, and Brown) and hair (Black, Brown, Blond, and Red) color predictions. We demonstrate that the HIrisPlex-S assay performs in full agreement with guidelines from the Scientific Working Group on DNA Analysis Methods (SWGDAM), achieving high sensitivity levels with a minimum 63pg DNA input. In addition to adding skin color to complete the pigmentation prediction system termed HIrisPlex-S, we successfully designed a Massively Parallel Sequencing (MPS) assay to complement the system and bring Next Generation Sequencing (NGS) to the forefront of forensic DNA analyses methods. Using Illumina’s MiSeq system enables the generation of HIrisPlex-S’s 41 variants using sequencing data that has the capacity to xiii better deconvolute mixtures and perform with even more sensitivity and accuracy. This transition opens the door for a plethora of new ways in which this physical appearance assay can grow as sequencing technology is not limited by variant number; therefore, in essence many more traits have the potential to be included in this one assay design. For now, the HIrisPlex-S design of 41 variants using MPS is being fully assessed according to SWGDAM validated guidelines; therefore, this design paves the way for Forensic DNA Phenotyping to be used in any forensic laboratory. This new and improved HIrisPlex-S system will have a profound impact on casework, missing persons cases, and anthropological cases, as it is relatively inexpensive to run, HIrisPlex-S is easy to use, developmentally validated and one of the largest systems freely available online for physical appearance prediction from DNA using the freely available online web tool found at https://hirisplex.erasmusmc.nl/. Lastly, moving forward in our aim to include additional traits for prediction from DNA, we contributed to a large-scale research collaboration to unearth variants associated with hair morphology. 1026 samples were successfully sequenced using an inhouse MPS design at 91 proposed hair morphological loci. From this reaction, we were able to contribute to the identification of significant correlations between the SNPs rs2219783, rs310642 and rs80293268 with categorical hair morphology: straight, wavy or curly.

Indiana University-Purdue University Indianapolis (IUPUI) / In the forensic science community, there is a vast need for tools to help assist investigations when standard DNA profiling methods are uninformative. Methods such as Forensic DNA Phenotyping (FDP) and proteomics aims to help this problem and provide aid in investigations when other methods have been exhausted. FDP is useful by providing physical appearance information, while proteomics allows for the examination of difficult samples, such as hair, to infer human identity and ancestry. To create a “biological eye witness” or develop informative probability of identity match statistics through proteomically inferred genetic profiles, it is necessary to constantly strive to improve these methods. Currently, two developmentally validated FDP prediction assays, ‘HIrisPlex’ and ‘HIrisplex-S’, are used on the capillary electrophoresis to develop a phenotypic prediction for eye, hair, and skin color based on 41 variants. Although highly useful, these assays are limited in their ability when used on the CE due to a 25 variant per assay cap. To overcome these limitations and expand the capacities of FDP, we successfully designed and validated a massive parallel sequencing (MPS) assay for use on both the ThermoFisher Scientific Ion Torrent and Illumina MiSeq systems that incorporates all HIrisPlex-S variants into one sensitive assay. With the migration of this assay to an MPS platform, we were able to create a semi-automated pipeline to extract SNP-specific sequencing data that can then be easily uploaded to the freely accessible online phenotypic prediction tool (found at https://hirisplex.erasmusmc.nl) and a mixture deconvolution tool with built-in read count thresholds. Based on sequencing reads counts, this tool can be used to assist in the separation of difficult two-person mixture samples and outline the confidence in each genotype call. In addition to FDP, proteomic methods, specifically in hair protein analysis, opens doors and possibilities for forensic investigations when standard DNA profiling methods come up short. Here, we analyzed 233 genetically variant peptides (GVPs) within hair-associated proteins and genes for 66 individuals. We assessed the proteomic methods ability to accurately infer and detect genotypes at each of the 233 SNPs and generated statistics for the probability of identity (PID). Of these markers, 32 passed all quality control and population genetics criteria and displayed an average PID of 3.58 x 10-4. A population genetics assessment was also conducted to identify any SNP that could be used to infer ancestry and/or identity. Providing this information is valuable for the future use of this set of markers for human identification in forensic science settings.

京都大学 / 0048 / 新制・課程博士 / 博士(医科学) / 甲第21024号 / 医科博第85号 / 新制||医科||6(附属図書館) / 京都大学大学院医学研究科医科学専攻 / (主査)教授 川上 浩司, 教授 黒田 知宏, 教授 森田 智視 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

The sexual assault kit backlog in the United States has become an increasing problem over the years. Combined with the number of kits laboratories receive with how it takes to extract the deoxyribonucleic acid (DNA) from the cells, it is hard for labs to keep up with the demand. The extraction method used is called differential extraction, where the epithelial cells from the victim are separated from the sperm cells from the perpetrator into different fractions. The Temperature Controlled Differential Extraction (TCDE) method is a novel procedure developed by the Cotton Lab at the Boston University School of Medicine and designed to decrease the extraction time while performing just as well, if not better, than traditional differential extraction methods. The TCDE method uses a series of temperature-controlled enzymes to lyse cells and purify the DNA extract. The purpose of this study is to compare this TCDE method to a method implemented by QIAGEN using the EZ1® Advanced biorobot for purification, which is used in many forensic laboratories. Ten female donors each received ten cotton swabs for vaginal cell collection; cotton swabs are typically found in sexual assault kits. Each swab then received either 5ng, 25ng, or 50ng of male DNA in the form of sperm cells. One half of the swab was processed using the TCDE procedure while the other half was processed using the EZ1® method. The TCDE method results in three fractions: the Epithelial Fraction (EF), the Material Fraction (MF), and the Sperm Fraction (SF). The EZ1® protocol was modified to include the additional MF. Results of both the quantitation data as well as the electropherograms (EPGs) produced are compared between the two methods. The quantitation data for the EF shows a variable amount of female DNA recovered due to the uncontrolled amount of female epithelial cells added to the swabs from the donors. The MF shows that large amounts of female epithelial DNA remain in the fraction for the EZ1® protocol and not the TCDE protocol because of the nuclease activity of one of the enzymes. The remaining male DNA on the MF can be used to compare to a known male profile, showing that there is valuable data potentially left behind. Regarding the SF, the EZ1® protocol resulted in a higher yield of DNA than the TCDE, however, the TCDE SF electropherograms are still able to be used for comparisons against known male profiles. The TCDE protocol cuts extraction time by almost half, and the quantitation results and EPGs prove that this method has the potential to become the new standard method of differential extraction.

Short Tandem Repeat (STR) analysis has become a valuable tool in identifying the source of biological stains, particularly from the investigation of sexual assault crimes. Difficulties in analysis arise primarily in the interpretation of mixed genotypes when cell separation of the sexual assailant's sperm from the victim's cells is incomplete. The forensic community continues to seek improvements in cell separation methods from mixtures for DNA typing. This report describes the use of laser microdissection (LMD) for the separation of pure populations of spermatozoa from two-donor cell mixtures. In this study, cell separation was demonstrated by microscopic identification of histologically stained spermatozoa and female buccal cell mixtures, and STR analysis of DNA obtained from the separated sperm cells. Clear profiles of the male donor were obtained with the absence of any additional alleles from the female donor. Five histological stains were evaluated for use with LMD and DNA analysis: hematoxylin/eosin, nuclear fast red/picroindigocarmine, methyl green, Wright's stain, and acridine orange. Hematoxylin/eosin out-performed all other stains however nuclear fast red/picroindigocarmine could be used satisfactorily with STR analysis. In addition, three DNA isolation methods were evaluated for LMD collected cells: QIAamp (Qiagen), microLYSIS (Microzone Ltd.) and Lyse-N-Go (Pierce Chemical Co.). MicroLYSIS performed poorly, yielding low levels of PCR product. Lyse-N-Go extraction was effective for the recovery of DNA from LMD collected sperm cells while QIAamp isolation performed best for the recovery of DNA from LMD collected epithelial cells. LMD is shown to be an effective, low-manipulation separation method that enables the recovery of sperm while excluding epithelial cell DNA.

<p>Forensic DNA databases are expanding in both use and range. In particular, the U.K. and U.S. are developing new techniques and policies in regards to their forensic DNA databases with the hope of increasing the role of forensic DNA databases in criminal investigations. Despite the goal of reducing crime, there are ethical concerns that arise with the ways in which these forensic DNA databases are being developed. This paper outlines the technical aspects of forensic DNA databases and then describes different conceptions of identity, using race as an example of a constructed identity that is relevant in the use of forensic DNA databases. Then it explains how forensic DNA databases construct a unique identity with the goal of ascribing this to people and groups. This ascribed identity is problematic, and different problems that are related to identity are discussed. Despite the benefits of forensic DNA databases, these problems are ethically relevant and as such, a series of policy recommendations are made with the aim of balancing the harms and benefits of forensic DNA databases.</p>

Forensic DNA databases are expanding in both use and range. In particular, the U.K. and U.S. are developing new techniques and policies in regards to their forensic DNA databases with the hope of increasing the role of forensic DNA databases in criminal investigations. Despite the goal of reducing crime, there are ethical concerns that arise with the ways in which these forensic DNA databases are being developed. This paper outlines the technical aspects of forensic DNA databases and then describes different conceptions of identity, using race as an example of a constructed identity that is relevant in the use of forensic DNA databases. Then it explains how forensic DNA databases construct a unique identity with the goal of ascribing this to people and groups. This ascribed identity is problematic, and different problems that are related to identity are discussed. Despite the benefits of forensic DNA databases, these problems are ethically relevant and as such, a series of policy recommendations are made with the aim of balancing the harms and benefits of forensic DNA databases.

It is common practice for DNA STR profiles to be analyzed using an analytical threshold (AT), but as more low template DNA (LT-DNA) samples are tested it has become evident that these thresholds do not adequately separate signal from noise. In order to confidently examine LT-DNA samples, the behavior and characteristics of the background noise of STR profiles must be better understood. Thus, the background noise of single source LT-DNA STR profiles were examined to characterize the noise distribution and determine how it changes with DNA template mass and injection time. Current noise models typically assume the noise is independent of fragment size but, given the tendency of the baseline noise to increase with template amount, it is important to establish whether the baseline noise is randomly found throughout the capillary electrophoresis (CE) run or whether it is situated in specific regions of the electropherogram. While it has been shown that the baseline noise of negative samples does not behave similarly to the baseline noise of profiles generated using optimal levels of DNA, the ATs determined using negative samples have shown to be similar to those developed with near-zero, low template mass samples. The distinction between low-template samples, where the noise is consistent regardless of target mass, and standard samples could be made at approximately 0.063 ng for samples amplified using the Identifiler^TM Plus amplification kit (29 cycle protocol), and injected for 5 and 10 seconds. At amplification target masses greater than 0.063 ng, the average noise peak height increased and began to plateau between 0.5 and 1.0 ng for samples injected for 5 and 10 seconds. To examine the time dependent nature of the baseline noise, the baselines of over 400 profiles were combined onto one axis for each target mass and each injection time. Areas of reproducibly higher noise peak heights were identified as areas of potential non-specific amplified product. When the samples were injected for five seconds, the baseline noise did not appear to be time dependent. However, when the samples were injected for either 10 or 20 seconds, there were three areas that exhibited an increase in noise; these areas were identified at 118 bases in green, 231 bases in yellow, and 106 bases in red. If a probabilistic analysis or AT is to be employed for DNA interpretation, consideration must be given as to how the validation or calibration samples are prepared. Ideally the validation data should include all the variation seen within typical samples. To this end, a study was performed to examine possible sources of variation in the baseline noise within the electropherogram. Specifically, three samples were prepared at seven target masses using four different kit lots, four capillary lots, in four amplification batches or four injection batches. The distribution of the noise peak heights in the blue and green channels for samples with variable capillary lots, amplifications, and injections were similar, but the distribution of the noise heights for samples with variable kit lots was shifted. This shift in the distribution of the samples with variable kit lots was due to the average peak height of the individual kit lots varying by approximately two. The yellow and red channels showed a general agreement between the distributions of the samples run with variable kit lots, amplifications, and injections, but the samples run with various capillary lots had a distribution shifted to the left. When the distribution of the noise height for each capillary was examined, the average peak height variation was less than two RFU between capillary lots. Use of a probabilistic method requires an accurate description of the distribution of the baseline noise. Three distributions were tested: Gaussian, log-normal, and Poisson. The Poisson distribution did not approximate the noise distributions well. The log-normal distribution was a better approximation than the Gaussian resulting in a smaller sum of the residuals squared. It was also shown that the distributions impacted the probability that a peak was noise; though how significant of an impact this difference makes on the final probability of an entire STR profile was not determined and may be of interest for future studies.

Sir Alec Jeffreys was the first to describe human identification with deoxyribonucleic acid (DNA) in his seminal work in 1985 (1); the result was the birth of forensic DNA analysis. Since then, DNA has become the primary substance used to conduct human identification testing. Forensic DNA analysis has evolved since the work of Jeffreys and now incorporates the analysis of 15 to 24 STR (short tandem repeat) locations, or loci (2-4). The simultaneous amplification and subsequent electrophoresis of tens of STR polymorphisms results in analysis that are highly discriminating. DNA target masses of 0.5 to 2 nanograms (ng) are sufficient to obtain a full STR profile (4); however, pertinent information can still be obtained if low copy numbers of DNA are collected from the crime scene or evidentiary material (4-9). Despite the sensitivity of polymerase chain reaction (PCR) - capillary electrophoresis (CE) based technology, low copy DNA signal can be difficult to interpret due to the preponderance of low signal-to-noise ratios. Due to the complicated nature of low template signal, optimization of the DNA laboratory process such that high-fidelity signal is regularly produced is necessary; studies designed to effectively hone in on optimized laboratory conditions are presented herein. The STR regions of a set of samples containing 0.0078 ng of DNA were amplified for 29 cycles; the amplified fragments were separated using two types of CE platforms: an ABI 3130 Genetic Analyzer and an ABI 3500 Genetic Analyzer. The result is a genetic trace, or electropherogram (EPG), comprised of three signal components that include noise, artifact, and allele. The EPGs were analyzed using two peak detection software programs. In addition, a tool, termed Simulating Evidentiary Electropherograms (SEEIt) (10, 11), was utilized to simulate EPG signal obtained when one copy of DNA is processed through the forensic pipeline. SEEIt was parameterized to simulate data corresponding to two laboratory scenarios: the amplification of a single copy of DNA injected on an ABI 3130 Genetic Analyzer and on an ABI 3500 Genetic Analyzer. In total, 20,000 allele peaks and 20,000 noise peaks were generated for each CE platform. Comparison of simulated and experimental data was used to elucidate features that are difficult to ascertain by experimental work alone. The data demonstrate that experimental signal obtained with the ABI 3500 platform results in signal that is, on average, a factor of four larger than signal obtained from the ABI 3130 platform. When a histogram of the signal is plotted, a multi modal distribution is observed. The first mode is hypothesized to be the result of noise, while the second, third, etc. modes are the signal obtained when one, two, etc. target DNA molecules are amplified. By evaluating the data in this way, full signal resolution between noise and allelic signal is visualized. Therefore, this methodology may be used to: 1) optimize post-PCR laboratory conditions to obtain excellent resolution between noise and allelic signal; and 2) determine an analytical threshold (AT) that results in few false detections and few cases of allelic dropout. A χ2 test for independence of the experimental signal in noise positions and the experimental signal within allele positions < 12 relative fluorescence units (RFU), i.e. signal in the noise regime, indicate the populations are not independent when sufficient signal-to-noise resolution is obtained. Once sufficient resolution is achieved, optimized ATs may be acquired by evaluating and minimizing the false negative and false positive detection rates. Here, a false negative is defined as the non-detection of an allele and a false positive is defined as the detection of noise. An AT of 15 RFU was found to be the optimal AT for samples injected on the ABI 3130 for at least 10 seconds (sec) as 99.42% of noise peaks did not exceed this critical value while allelic dropout was kept to a minimum, 36.97%, at this AT. Similarily, in examining signal obtained from the ABI 3500, 99.41% and 99.0% of noise fell under an AT of 50 RFU for data analyzed with GeneMapper ID-X (GM) and OSIRIS (OS), respectively. Allelic dropout was 36.34% and 36.55% for GM and OS, respectively, at this AT.