Analysis of homozygous allele mismatches in paternity tests with massively parallel sequencing.

In paternity testing, short tandem repeats (STRs) allele mismatches are often detected. Nowadays, polymerase chain reaction- and capillary electrophoresis (CE)-based STR genotyping is the most commonly used method to distinguish alleles based on their length. However, it could not detect alleles of the same size with sequence differences. Massively parallel sequencing (MPS) can determine not only allele sizes but also sequences, which could explain the causes of allele mismatches. Additionally, more types of genetic markers can be detected in a single assay, which increases the discriminatory power and facilitates the analysis of paternity tests. In this study, we analyzed 11 cases with homozygous allele mismatches from routine DNA trio paternity tests using the CE platform. Samples were sequenced using the ForenSeq DNA Signature Prep Kit and the MiSeq FGx Sequencing System. The results show that of the eight father-child mismatch cases and three mother-child mismatch cases, five cases with D5S818 and D8S1179 and one case at D13S317 were classified as non-amplification. The other three cases and two cases could be defined as mutations. This study suggests that MPS-based STR genotyping can provide additional information that allows more accurate interpretation of allelic mismatches in paternity testing.

DNA and protein analyses of hair in forensic genetics.

Hair is one of the most common pieces of biological evidence found at a crime scene and plays an essential role in forensic investigation. Hairs, especially non-follicular hairs, are usually found at various crime scenes, either by natural shedding or by forcible shedding. However, the genetic material in hairs is usually highly degraded, which makes forensic analysis difficult. As a result, the value of hair has not been fully exploited in forensic investigations and trials. In recent years, with advances in molecular biology, forensic analysis of hair has achieved remarkable strides and provided crucial clues in numerous cases. This article reviews recent developments in DNA and protein analysis of hair and attempts to provide a comprehensive solution to improve forensic hair analysis.

Rapid and visual detection of specific bacteria for saliva and vaginal fluid identification with the lateral flow dipstick strategy.

Identification of body fluids is critical for crime scene reconstruction, and a source of investigation source of investigative leads. In recent years, microbial DNA analysis using sequencing and quantitative real-time polymerase chain reaction have been used to identify body fluids. However, these techniques are time-consuming, expensive, and require complex workflows. In this study, a new method for simultaneous detection of Streptococcus salivarius and Lactobacillus crispatus using polymerase chain reaction (PCR) in combination with a lateral flow dipstick (LFD) was developed to identify saliva and vaginal fluid in forensic samples. LFD results can be observed with the naked eye within 3 min with a sensitivity of 0.001 ng/µL DNA. The PCR-LFD assay was successfully used to detect S. salivarius and L. crispatus in saliva and vaginal fluid respectively, and showed negative results in blood, semen, nasal fluid, and skin. Moreover, saliva and vaginal fluid were detectable even at an extremely high mixing ratio of sample DNA (1:999). Saliva and vaginal fluid were identified in various mock forensic samples. These results indicate that saliva and vaginal fluid can be effectively detected by identifying S. salivarius and L. crispatus, respectively. Furthermore, we have shown that DNA samples used to identify saliva and vaginal fluid can also provide a complete short tandem repeat (STR) profile when used as source material for forensic STR profiling. In summary, our results suggest that PCR-LFD is a promising assay for rapid, simple, reliable, and efficient identification of body fluids.

Performance of a 74-Microhaplotype Assay in Kinship Analyses.

Microhaplotypes (MHs) consisting of multiple SNPs and indels on short stretches of DNA are new and interesting loci for forensic genetic investigations. In this study, we analysed 74 previously defined MHs in two of the populations that our laboratory provides with forensic genetic services, Danes and Greenlanders. In addition to the 229 SNPs that originally made up the 74 MHs, 66 SNPs and 3 indels were identified in the two populations, and 45 of these variants were included in new definitions of the MHs, whereas 24 SNPs were considered rare and of little value for case work. The average effective number of alleles (Ae) was 3.2, 3.0, and 2.6 in Danes, West Greenlanders, and East Greenlanders, respectively. High levels of linkage disequilibrium were observed in East Greenlanders, which reflects the characteristics of this population that has a small size, and signs of admixture and substructure. Pairwise kinship simulations of full siblings, half-siblings, first cousins, and unrelated individuals were performed using allele frequencies from MHs, STRs and SNPs from Danish and Greenlandic populations. The MH panel outperformed the currently used STR and SNP marker sets and was able to differentiate siblings from unrelated individuals with a 0% false positive rate and a 1.1% false negative rate using an LR threshold of 10,000 in the Danish population. However, the panel was not able to differentiate half-siblings or first cousins from unrelated individuals. The results generated in this study will be used to implement MHs as investigative markers for relationship testing in our laboratory.

Circadian metabolites for evaluating the timing of bloodstain deposition: A preliminary study.

Metabolites, as products of cellular metabolism, can provide a wealth of biological information and are less susceptible to degradation than other biomarkers due to their low molecular weight. Due to these properties, metabolites can be used as valuable biomarkers for forensic investigations. Knowing the timing of deposition of bloodstain could help to reconstruct crime scenes, draw conclusions about the time of the crime, and narrow down the circle of possible suspects. Previous studies have indicated that the concentration of some metabolites in blood is subject to circadian changes. However, the circadian metabolites of bloodstains have been still unclear. A total of sixty-four bloodstain samples were prepared under real conditions in three time categories (morning/noon (09:00 h ∼ 17:00 h), afternoon/evening (18:00 h ∼ 23:00 h) and night/early morning (24:00 h ∼ 08:00 h)). Fifty metabolites of bloodstains with significant differences were identified in the three time categories. Twenty-eight of these metabolites exhibited significant circadian changes. Finally, three independently contributing circadian metabolites were selected to build the logistic regression model, with an area under the curve of 0.91, 0.84 and 0.87 for the prediction of bloodstain deposition time in the morning/noon, afternoon/evening and night/early morning, respectively. The study indicated that circadian metabolites can be used for evaluating the timing of bloodstain deposition. This would provide a valuable perspective for analyzing the deposition time of biological traces in forensic investigations.

Application of Microbiome in Forensics.

Recent advances in next-generation sequencing technologies and improvements in bioinformatics have expanded the scope of microbiome analysis as a forensic tool. Microbiome research is concerned with the study of the compositional profile and diversity of microbial flora as well as the interactions between microbes, hosts, and the environment. It has opened up many new possibilities for forensic analysis. In this review, we discuss various applications of microbiome in forensics, including identification of individuals, geolocation inference, and post-mortem interval (PMI) estimation.

Tracing recent outdoor geolocation by analyzing microbiota from shoe soles and shoeprints even after indoor walking.

The microbial communities on shoe soles and shoeprints could carry microbial information about where someone walked. This is possible evidence to link a suspect in a crime case to a geographic location. A previous study had shown that the microbiota found on shoe soles depend on the microbiota of the soil on which people walk. However, there is a turnover of microbial communities on shoe soles during walking. The impact of microbial community turnover on tracing recent geolocation from shoe soles has not been adequately studied. In addition, it is still unclear whether the microbiota of shoeprints can be used to determine recent geolocation. In this preliminary study, we investigated whether the microbial characteristics of shoe soles and shoeprints can be used to trace geolocation and whether this information can be destroyed by walking on indoor floors. In this study, participants were asked to walk outdoors on exposed soil, then walk indoors on a hard wood floor. High-throughput sequencing of the 16S rRNA gene was performed to characterize the microbial communities of shoe soles, shoeprints, indoor dust, and outdoor soil. Samples of shoe soles and shoeprints were collected at steps 5, 20, and 50 while walking indoors. The PCoA result showed that the samples were clustered by geographic origin. The shoeprint showed a more rapid turnover of microbial community than the shoe sole during indoor walking. The result of FEAST showed that the microbial communities of shoe sole and shoeprint were mainly (shoe sole, 86.21∼92.34 %; shoeprint, 61.66∼90.41 %) from the soil of the outdoor ground where the individual recently walked, and a small portion (shoe sole, 0.68∼3.33 %; shoeprint, 1.43∼27.14 %) from the indoor dust. Based on the matching of microbial communities between geolocation and shoe sole or shoeprint, we were able to infer the recent geolocation of the individual with relatively high accuracy using the random forest prediction model (shoe sole: 100.00 %, shoeprint: 93.33∼100.00 %). Overall, we are able to accurately infer the geolocation of an individual's most recent outdoor walk based on the microbiota of shoe sole and shoeprint, even though these microbiotas show a turnover when walking indoor floor. The pilot study was expected to provide a potential method for tracing recent geolocation of suspects.

Estimation of bloodstain deposition time within a 24-h day-night cycle with rhythmic mRNA based on a machine learning algorithm.

Estimating the time that bloodstains are left at a crime scene can provide invaluable evidence for law enforcement investigations, including determining the time of the crime, linking the perpetrator to the crime scene, narrowing the pool of possible suspects, and verifying witness statements. There have been some attempts to estimate the time since deposition of bloodstains, i.e., how much time has passed since the bloodstain was left at a crime scene. However, most studies focus on the time interval of days. As far as we know, previous study have been conducted to estimate the deposition time of blood within a 24-h day-night cycle. To date, there is a lack of studies on whether rhythmic mRNA of blood is suitable for bloodstain samples. In this study, we estimated the bloodstain deposition time within a 24-h day-night cycle based on the expression of messenger RNAs (mRNAs) by real-time quantitative polymerase chain reaction. Bloodstain samples were prepared from eight individuals at eight time points under real and uncontrolled conditions. Four mRNAs expressed rhythmically and were used to construct a regression model using the k-nearest neighbor (KNN) algorithm, resulting in a mean absolute error of 3.92 h. Overall, using the rhythmic mRNAs, a machine learning model was developed which has allowed us to predict the deposition time of bloodstains within the 24-h day-night cycle in East Asian populations. This study demonstrates that mRNA biomarkers can be used to estimate the bloodstain deposition time within a 24-h period. Furthermore, rhythmic mRNA biomarkers provide a potential method and perspective for estimating the deposition time of forensic traces in forensic investigation. Case samples in forensic analysis are usually limited or degraded, so the stability and sensitivity of rhythmic biomarkers need to be further investigated.

Changes in Gut Microbiota and Metabolites in Papillary Thyroid Carcinoma Patients Following Radioactive Iodine Therapy.

Purpose: Radioactive iodine therapy is administered through oral route, which is accumulated and absorbed in the intestine. However, its effects on the intestine remain unclear. In this study, we investigated the changes in the gut microbiota and metabolites following radioactive iodine therapy. Patients and Methods: A total of 76 stool samples from the same 38 patients were collected at the start of radioactive iodine therapy and three days following the therapy. Stool microbiota and metabolites were detected using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry. Results: Enterobacteriales, Enterobacteriaceae and Escherichia-Shigella were elevated in most patients (27/38) following the therapy. The levels of 2-hydroxyundec-7-enoylcarnitine were significantly lower, whereas those of 5-dehydroavenasterol, butylisopropylamine, and salsoline-1-carboxylate were higher following the therapy. The relative abundance of Escherichia-Shigella was negatively correlated with 2-hydroxyundec-7-enoylcarnitine level (r2 = -0.661, P = 0.009). Functional pathways were predicted to be involved in amino acid and lipid metabolism following the therapy. Particularly, phenylalanine, linoleic acid, sphingolipid, purine, and alpha-linolenic acid metabolism were the main metabolic pathways. Conclusion: Gut microbiota was disturbed following radioactive iodine therapy, with increased Escherichia-Shigella. Processes associated with energy production seems to be impacted following the therapy, with significantly decreased 2-hydroxyundec-7-enoylcarnitine level. Meanwhile, some metabolites and functional pathways may have a positive effect on intestinal homeostasis, and may be related to the repair and promotion of gut recovery following the therapy. This study provides a basic foundation to explore how radioactive iodine affects gut microbiota and metabolites, and how gut function is regulated in response to radioactive iodine therapy.

Sequencing of human identification markers in an Uyghur population using the MiSeq FGxTM Forensic Genomics System.

Massively parallel sequencing (MPS) offers a useful alternative to capillary electrophoresis (CE) based analysis of human identification markers in forensic genetics. By sequencing short tandem repeats (STRs) instead of determining the fragment lengths by CE, the sequence variation within the repeat region and the flanking regions may be identified. In this study, we typed 264 Uyghur individuals using the MiSeq FGx™ Forensic Genomics System and Primer Mix A of the ForenSeq™ DNA Signature Prep Kit that amplifies 27 autosomal STRs, 25 Y-STRs, seven X-STRs, and 94 HID-SNPs. STRinNGS v.1.0 and GATK 3.6 were used to analyse the STR regions and HID-SNPs, respectively. Increased allelic diversity was observed for 33 STRs with the PCR-MPS assay. The largest increases were found in DYS389II and D12S391, where the numbers of sequenced alleles were 3-4 times larger than those of alleles determined by repeat length alone. A relatively large number of flanking region variants (28 SNPs and three InDels) were observed in the Uyghur population. Seventeen of the flanking region SNPs were rare, and 12 of these SNPs had no accession number in dbSNP. The combined mean match probability and typical paternity index based on 26 sequenced autosomal STRs were 3.85E-36 and 1.49E + 16, respectively. This was 10 000 times lower and 1 000 times higher, respectively, than the same parameters calculated from STR repeat lengths.Key PointsSequencing data on STRs and SNPs used for human identification are presented for the Uyghur population.STRinNGS v.1.0 was used to analyse the flanking regions of STRs.The concordance between PCR-CE and PCR-MPS results was 99.86%.Detection of sequence variation in STRs and their flanking regions increased the allelic diversity.

Corrigendum: The heart of silk road "Xinjiang", its genetic portray, and forensic parameters inferred from autosomal STRs.

[This corrects the article DOI: 10.3389/fgene.2021.760760.].

The Heart of Silk Road "Xinjiang," Its Genetic Portray, and Forensic Parameters Inferred From Autosomal STRs.

The Xinjiang Uyghur Autonomous Region of China (XUARC) harbors almost 50 ethnic groups including the Uyghur (UGR: 45.84%), Han (HAN: 40.48%), Kazakh (KZK: 6.50%), Hui (HUI: 4.51%), Kyrgyz (KGZ: 0.86%), Mongol (MGL: 0.81%), Manchu (MCH: 0.11%), and Uzbek (UZK: 0.066%), which make it one of the most colorful regions with abundant cultural and genetic diversities. In our previous study, we established allelic frequency databases for 14 autosomal short tandem repeats (STRs) for four minority populations from XUARC (MCH, KGZ, MGL, and UZK) using the AmpFlSTR® Identifiler PCR Amplification Kit. In this study, we genotyped 2,121 samples using the GoldenEye™ 20A Kit (Beijing PeopleSpot Inc., Beijing, China) amplifying 19 autosomal STR loci for four major ethnic groups (UGR, HAN, KZK, and HUI). These groups make up 97.33% of the total XUARC population. The total number of alleles for all the 19 STRs in these populations ranged from 232 (HAN) to 224 (KZK). We did not observe any departures from the Hardy-Weinberg equilibrium (HWE) in these populations after sequential Bonferroni correction. We did find minimal departure from linkage equilibrium (LE) for a small number of pairwise combinations of loci. The match probabilities for the different populations ranged from 1 in 1.66 × 1023 (HAN) to 6.05 × 1024 (HUI), the combined power of exclusion ranged from 0.999 999 988 (HUI) to 0.999 999 993 (UGR), and the combined power of discrimination ranged from 0.999 999 999 999 999 999 999 983 (HAN) to 0.999 999 999 999 999 999 999 997 (UGR). Genetic distances, principal component analysis (PCA), STRUCTURE analysis, and the phylogenetic tree showed that genetic affinity among studied populations is consistent with linguistic, ethnic, and geographical classifications.

STRinNGS v2.0: Improved tool for analysis and reporting of STR sequencing data.

High throughput sequencing of multiplexed PCR amplicons with Short Tandem Repeats (STRs) requires software solutions that sort the information and allow a comprehensive overview of the results without overwhelming the data analyst with details. Here, we present an updated version (2.0) of the STR analysis tool STRinNGS. It is freely available as a Docker image or zip file ready for downloading. STRinNGS predicts genotypes using criteria for read depth, noise, flanking region lengths, mismatches in the flanking regions, locus balance, and heterozygote balance. Warning flags highlight suspicious genotypes as well as suspicious sequences that are not identified as either noise or alleles in the result table used for the manual analysis. STRinNGS analyses both the STR and the flanking regions, and names the alleles according to the STRidER guidelines as well as an in-house nomenclature that also include variants in the flanking regions. Furthermore, STRinNGS generates files with analysed data in a format that may be uploaded directly to the STRidER database. We re-analysed 627 sample files from eight different MiSeq FGx runs with STRinNGS v2.0. The samples were previously typed with the ForenSeq™ Signature Prep Kit and analysed with STRinNGS v1.0 and the Universal Analysis Software. Apart from three poorly performing loci with large heterozygote imbalances (Penta E and D22S1045) or frequent single nucleotide errors (DYS461), only 58 genotype calls (0.2 %) had to be manually corrected and only 14 genotype calls were discordant with the previous analyses. The discordant calls were primarily caused by manual oversights and in every case, the STRinNGS v2.0 analysis was correct.