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In this study, 172 Single-Nucleotide Polymorphisms (SNPs) (94 identity-informative SNPs, 56 ancestry-informative SNPs, and 22 phenotypic-informative SNPs) included in the ForenSeq™ DNA Signature Prep kit/DNA Primer Mix B (Verogen) were used for genotyping DNA samples from a population of twenty-one unrelated subjects, native to Northeast Italy. SNP sequencing was performed with the MiSeq FGx™ Forensic Genomics System (Illumina-Verogen), and data were analyzed using the Universal Analysis Software (UAS) v1.2. Raw data underwent further examination with STRait Razor v3 (SRv3) to compare the target SNPs’ genotype calls made with UAS and to identify the presence of microhaplotypes (MHs) due to SNPs associated with the same target SNP’s amplicon. The allele (haplotype) frequencies, Hardy–Weinberg equilibrium, linkage disequilibrium, number of effective alleles (Ae), and relevant forensic statistic parameters were calculated. Among the 172 SNPs evaluated, 45 unique microhaplotypes were found, comprising a novel sequence variant never previously described. The presence of MHs resulted in an 8.00% rise in the typologies of unique sequences, leading to changes in Ae. Notably, for 12 out of the 94 iiSNPs, the values of Ae exceeded 2.00, which is generally associated with a higher expected heterozygosity and increased power of discrimination.

Spain suffered a Civil War between 1936 and 1939 that ended with the victory of the National Forces led by General Franco. Once the Spanish Civil War ended, 2238 subjects were executed and buried in several mass graves in the Cemetery of Paterna, one of Spain's largest mass grave sites. Efforts to locate and identify all the victims of the mass graves of the Paterna cemetery are ongoing, but the actual data of the percentage of DNA identifications remains uncertain. Following this, we conducted a meta-research study including 15 mass graves and 933 subjects to determine the DNA identification rates in the mass graves of the Paterna cemetery. We found that the total proportion of identified subjects in the mass graves was 15.9 % (95 % CI: 10.0–22.9). Moreover, we found that the model between the identification success rate (ISR) and the number of relatives that donated DNA (NRTDD) in the mass graves of the cemetery of Paterna was ISR = NRTDD−0.424. Results obtained about the proportion of identified subjects and the model between the ISR and the NRTDD imply the need for a scientific reflection between all the research groups involved in the identification tasks to modify deficiencies and update identification protocols to obtain better future results. •More than 2200 subjects lay in mass graves in the Cemetery of Paterna.•Fifteen mass graves with 933 subjects were analyzed.•The proportion of identified subjects was 15.9 % (95 % CI: 10.0–22.9).•The model between the ISR and the NRTDD was: ISR = NRTDD-0.424.

In criminal investigations, forensic scientists need to evaluate DNA mixtures. The estimation of the number of contributors and evaluation of the contribution of a person of interest (POI) from these samples are challenging. In this study, we developed a new open-source software \"Kongoh\" for interpreting DNA mixture based on a quantitative continuous model. The model uses quantitative information of peak heights in the DNA profile and considers the effect of artifacts and allelic drop-out. By using this software, the likelihoods of 1-4 persons' contributions are calculated, and the most optimal number of contributors is automatically determined; this differs from other open-source software. Therefore, we can eliminate the need to manually determine the number of contributors before the analysis. Kongoh also considers allele- or locus-specific effects of biological parameters based on the experimental data. We then validated Kongoh by calculating the likelihood ratio (LR) of a POI's contribution in true contributors and non-contributors by using 2-4 person mixtures analyzed through a 15 short tandem repeat typing system. Most LR values obtained from Kongoh during true-contributor testing strongly supported the POI's contribution even for small amounts or degraded DNA samples. Kongoh correctly rejected a false hypothesis in the non-contributor testing, generated reproducible LR values, and demonstrated higher accuracy of the estimated number of contributors than another software based on the quantitative continuous model. Therefore, Kongoh is useful in accurately interpreting DNA evidence like mixtures and small amounts or degraded DNA samples.

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.

Pakistan is located at an important cross-road of human history and has been a passageway for many invaders and dynasties in the past. The historic human migrations across this country have resulted in a blend of ancient civilizations, which are still reflected in the current socio-cultural fabrication of this population. This makes Pakistan an ideal country to study the genetic differentiation and various other genomic aspects of a human population.

This paper presents a system for the multiplex amplification of 15 loci, known as I-DNA1, which combines mini and midiSTR technology, with amplicon sizes ranging from 49 to 297 bp. I-DNA1 analyses all the STR loci included in the CODIS and the Interpol Standard Set of loci, nine of the ten European core loci and seven of the eight German core loci, making it suitable for use in identifying humans. Moreover, its high sensitivity and the small size of its amplicons mean that I-DNA1 is potentially highly useful for analysing highly degraded and/or very small DNA samples.

Candida colonization of the oral cavity increases in the elderly. A major predisposing condition is denture use, which also increases in the elderly. To test whether the increase in colonization is age-related in a fashion independent of denture use, we analyzed the frequency (incidence) of carriage, the intensity of carriage, the multiplicity of species, and the genetic relatedness of strains in the oral cavities of 93 test subjects separated into the three age groups: 60 to 69 yr, 70 to 79 yr, and ≥ 80 yr. Each age group was further subdivided into subjects with and without dentures, and into males and females. The results demonstrate that the frequency of carriage, the intensity of carriage, and multispecies carriage all increase as a function of age and differ according to gender, in both cases independent of denture use, suggesting that the natural suppression of yeast carriage in the oral cavity breaks down in the elderly. In addition, it is demonstrated that Candida glabrata colonizes the oral cavities of elderly individuals without dentures only after 80 yr of age, suggesting that there are age-related compromising conditions other than denture use in this most elderly age group.

AFLP is a DNA fingerprinting technique frequently used in plant and animal sciences. A drawback of the technique is the occurrence of multiple DNA fragments of the same length in a single AFLP lane, which we name a collision. In this article we quantify the problem. The well-known birthday problem plays a role. Calculation of collision probabilities requires a fragment length distribution (fld). We discuss three ways to estimate the fld: based on theoretical considerations, on in-silico determination using DNA sequence data from Arabidopsis thaliana, or on direct estimation from AFLP data. In the latter case we use a generalized linear model with monotone smoothing of the fragment length probabilities. Collision probabilities are calculated from two perspectives, assuming known fragment counts and assuming known band counts. We compare results for a number of fld's, ranging from uniform to highly skewed. The conclusion is that collisions occur often, with higher probabilities for higher numbers of bands, for more skewed distributions, and, to a lesser extent, for smaller scoring ranges. For a typical plant genome an AFLP with 19 bands is likely to contain the first collision. Practical implications of collisions are discussed. AFLP examples from lettuce and chicory are used for illustration.

AFLP is a DNA fingerprinting technique, resulting in binary band presence-absence patterns, called profiles, with known or unknown band positions. We model AFLP as a sampling procedure of fragments, with lengths sampled from a distribution. Bands represent fragments of specific lengths. We focus on estimation of pairwise genetic similarity, defined as average fraction of common fragments, by AFLP. Usual estimators are Dice (D) or Jaccard coefficients. D overestimates genetic similarity, since identical bands in profile pairs may correspond to different fragments (homoplasy). Another complicating factor is the occurrence of different fragments of equal length within a profile, appearing as a single band, which we call collision. The bias of D increases with larger numbers of bands, and lower genetic similarity. We propose two homoplasy- and collision-corrected estimators of genetic similarity. The first is a modification of D, replacing band counts by estimated fragment counts. The second is a maximum likelihood estimator, only applicable if band positions are available. Properties of the estimators are studied by simulation. Standard errors and confidence intervals for the first are obtained by bootstrapping, and for the second by likelihood theory. The estimators are nearly unbiased, and have for most practical cases smaller standard error than D. The likelihood-based estimator generally gives the highest precision. The relationship between fragment counts and precision is studied using simulation. The usual range of band counts (50-100) appears nearly optimal. The methodology is illustrated using data from a phylogenetic study on lettuce.

The 2p rule is commonly used to interpret partial DNA profiles where dropout may have occurred. Recently this approach has been questioned in court. We investigate the performance of this rule, and give conditions under which it may be relied upon. Our analysis leads us to recommend an alternative approach. This may be used in all circumstances or reserved for those circumstances under which the 2p rule is not conservative.