Precision DNA Mixture Interpretation with Single-Cell Profiling

Wet-lab based studies have exploited emerging single-cell technologies to address the challenges of interpreting forensic mixture evidence. However, little effort has been dedicated to developing a systematic approach to interpreting the single-cell profiles derived from the mixtures. This study is the first attempt to develop a comprehensive interpretation workflow in which single-cell profiles from mixtures are interpreted individually and holistically. In this approach, the genotypes from each cell are assessed, the number of contributors (NOC) of the single-cell profiles is estimated, followed by developing a consensus profile of each contributor, and finally the consensus profile(s) can be used for a DNA database search or comparing with known profiles to determine their potential sources. The potential of this single-cell interpretation workflow was assessed by simulation with various mixture scenarios and empirical allele drop-out and drop-in rates, the accuracies of estimating the NOC, the accuracies of recovering the true alleles by consensus, and the capabilities of deconvolving mixtures with related contributors. The results support that the single-cell based mixture interpretation can provide a precision that cannot beachieved with current standard CE-STR analyses. A new paradigm for mixture interpretation is available to enhance the interpretation of forensic genetic casework.

Uncertainty in estimating the number of contributors from simulated DNA mixture profiles, with and without allele dropout, from Chinese, Malay, Indian, and Caucasian ethnic populations

Determining the number of contributors (NOC) accurately in a forensic DNA mixture profile can be challenging. To address this issue, there have been various studies that examined the uncertainty in estimating the NOC in a DNA mixture profile. However, the focus of these studies lies primarily on dominant populations residing within Europe and North America. Thus, there is limited representation of Asian populations in these studies. Further, the effects of allele dropout on the NOC estimation has not been explored. As such, this study assesses the uncertainty of NOC in simulated DNA mixture profiles of Chinese, Malay, and Indian populations, which are the predominant ethnic populations in Asia. The Caucasian ethnic population was also included to provide a basis of comparison with other similar studies. Our results showed that without considering allele dropout, the NOC from DNA mixture profiles derived from up to four contributors of the same ethnic population could be estimated with confidence in the Chinese, Malay, Indian and Caucasian populations. The same results can be observed on DNA mixture profiles originating from a combination of differing ethnic populations. The inclusion of an overall 30% allele dropout rate increased the probability (risk) of underestimating the NOC in a DNA mixture profile; even a 3-person DNA mixture profile has a > 99% risk of underestimating the NOC as two or fewer contributors. However, such risks could be mitigated when the highly polymorphic SE33 locus was included in the dataset. Lastly there was a negligible level of risk in misinterpreting the NOC in a mixture profile as deriving from a single source profile. In summary, our studies showcased novel results representative of the Chinese, Malay, and Indian ethnic populations when examining the uncertainty in NOC estimation in a DNA mixture profile. Our results would be useful in the estimation of NOC in a DNA mixture profile in the Asian context.

Analyzing Low-Level mtDNA Heteroplasmy—Pitfalls and Challenges from Bench to Benchmarking

Massive parallel sequencing technologies are promising a highly sensitive detection of low-level mutations, especially in mitochondrial DNA (mtDNA) studies. However, processes from DNA extraction and library construction to bioinformatic analysis include several varying tasks. Further, there is no validated recommendation for the comprehensive procedure. In this study, we examined potential pitfalls on the sequencing results based on two-person mtDNA mixtures. Therefore, we compared three DNA polymerases, six different variant callers in five mixtures between 50% and 0.5% variant allele frequencies generated with two different amplification protocols. In total, 48 samples were sequenced on Illumina MiSeq. Low-level variant calling at the 1% variant level and below was performed by comparing trimming and PCR duplicate removal as well as six different variant callers. The results indicate that sensitivity, specificity, and precision highly depend on the investigated polymerase but also vary based on the analysis tools. Our data highlight the advantage of prior standardization and validation of the individual laboratory setup with a DNA mixture model. Finally, we provide an artificial heteroplasmy benchmark dataset that can help improve somatic variant callers or pipelines, which may be of great interest for research related to cancer and aging.

Effect of Fragmented DNA From Plant Pathogens on the Protection Against Wilt and Root Rot of Capsicum annuum L. Plants

Chili pepper (Capsicum annuum L.) production is affected by wilt and root rot, the most devastating disease caused by the pathogen complex of oomycete Phytophthora capsici Leon and the fungi Fusarium oxysporum Schlecht and Rhizoctonia solani Kühn, infecting roots, stems, leaves, and fruits. Fungicides are currently inefficient against this disease and have a high environmental impact. The use of elicitors is a sustainable alternative for inducing resistance to wilting and root rot. DNA fragments of an organism’s own origin (conspecific or self-DNA) have shown the ability to inhibit growth and activate defense mechanisms in some plant species. In this investigation, the effect of the fragmented DNA mixture of Phytophthora capsici L., Fusarium oxysporum S., and Rhizoctonia solani K. on the protection against wilt and root rot of Capsicum annuum L. plants was evaluated. Changes in plant performance, phenolics, and flavonoids contents, as well as gene expression involved in the production of defense metabolites after the fragmented and unfragmented DNA mixture in three concentrations (20, 60, and 100 μg mL–1) in chili peppers, were studied. The results obtained showed a decrease in plant height in 60 and 100 μg mL–1 concentrations in absence of pathogens. Moreover, the treatment with fragmented DNA 100 μg mL–1 showed significant increase in the content of phenolic compounds and total flavonoids as well as gene expression associated to plant defense in comparison with control plants. Interestingly, foliar application of DNA fragments of the pathogen complex to a concentration of 100 μg mL–1 caused a 40% decrease in the mortality of infected plants with the pathogens at 30 days post-inoculation compared with control plants inoculated with the pathogen complex but not sprayed with DNA fragments. These results suggested a perspective for application of fragmented DNA of these pathogens at the agricultural level in crop protection strategies to cope with wilt and root rot in Capsicum.