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A Survey of Newer Gene Probing Techniques
Published in Victor A. Bernstam, Pocket Guide to GENE LEVEL DIAGNOSTICS in Clinical Practice, 2019
Variability in the estimates of the length of allele fragments (usually within 0.6 to 1.0%) due to the resolving power of agarose electrophoresis used in separating the restricted fragments in single-locus probe testing must be entered into the statistical evaluation of the observed frequency of a restriction fragment in the population. An averaging approach that combines close alleles into the so-called “frequency bins” is used. Advantages of using DNA probes have been clearly demonstrated in a case of disputed paternity when seven probes had been used to produce the cumulative paternity index of 1.4 × 106 that was 316 times higher than that obtainable from the 23 standard blood group markers and HLA.
Analysis and Interpretation
Published in John M. Wayne, Cynthia A. Schandl, S. Erin Presnell, Forensic Pathology Review, 2017
John M. Wayne, Cynthia A. Schandl, S. Erin Presnell
The correct answer is E. 7402. The combined paternity index, also known as genetic odds in favor of paternity, is calculated by determining which genetic marker each person has in common. This is done by looking at each “system” and seeing if a common locus exists. For example, the D8S1179 system has a shared allele (in this case, 14) between the child and alleged father, so it is used in the calculation. Once it is determined which systems are matched then the paternity index is multiplied by each other. The paternity index is a calculated value generated for a single genetic marker or locus (chromosomal location or site of DNA sequence of interest). In our example, all of the systems had one shared allele and are multiplied together yielding 7402.38 as the product that rounds to 7402. Of note the AMEL system does not have a number since it is used to define sex of the individual and is assumed to be 1. Another way of saying this is that the odds are 7402 to 1 that the alleged father is not the father. All of the other answers are incorrect as they do not yield the correct calculation. Choice A is the probability of paternity, not the combined paternity index. Choice B is the indices added instead of multiplied.
Mutational analysis of 16 STR markers in the Slovak population
Published in Annals of Human Biology, 2022
Zdenko Červenák, Filip Červenák, Marian Baldovič, Andrea Patlevičová, Soňa Masnicová
In this study, we estimated the mutation rates of 16 STR markers (15 CODIS plus SE33) and showed that they vary from 0.000 to 0.0068%. The highest overall mutation rate was observed for locus SE33 and the ratio of paternal versus maternal mutations was 4.25:1. Moreover, the numbers of gains and losses of repeat units were nearly equal. The comparison of overall mutation rates with those of other worldwide populations showed significant differences at two STR markers (vWA, D8S1179). Taken together, since the STR mutations play an important role in paternity testing and mutation rates seem to vary between the different populations, the mutation rates of all 16 STR markers included in our study can serve to strengthen the correct paternity index calculations and increase reliability of paternity testing results in Slovakia.
Genetic admixture history and forensic characteristics of Turkic-speaking Kyrgyz population via 23 autosomal STRs
Published in Annals of Human Biology, 2019
Pengyu Chen, Xing Zou, Biao Wang, Mengge Wang, Guanglin He
Allele frequency and forensic parameter estimation of 23 A-STRs were conducted using STRAF (Gouy and Zieger 2017). The following parameters are considered and include typical paternity index (TPI), match probability (PM), power of discrimination (PD), polymorphism information content (PIC), and power of exclusion (PE). We used Arlequin v.3.5 (Excoffier and Lischer 2010) to evaluate the status of Hardy-Weinberg Equilibrium (HWE) and Linkage Disequilibrium (LD), as well as to calculate the observed heterozygosity (Ho) and expected heterozygosity (He). Pairwise Reynolds genetic distances among 56 worldwide populations based on the allele frequency correlations and Fst genetic distances among 15 Eurasian populations based on raw data were subsequently calculated using the Phylogeny Inference Packages (PHYLIP) version 3.5 and STRAF, respectively. Genetic relationships were further inferred from the principal component analysis using the Multivariate Statistical Package (MVSP) version 3.22 software (Kovach 2007) and multidimensional scaling plots (MDS) using IBM SPSS Statistics 21 (Hansen 2005). The phylogenetic relationships between our studied Kyrgyz and other reference populations were constructed using the neighbor-joining framework implemented in the Molecular Evolutionary Genetics Analysis Version 7.0 (Mega 7.0) (Kumar et al. 2016). To dissect the individual ancestry of Kyrgyz, we conducted the model-based STRUCTURE analysis with models of “LOCPRIOR” and “correlated allele frequencies” (Evanno et al. 2005).
Population genetic polymorphism and mutation analysis of 19 autosomal STR loci in Jiangsu Han individuals in Eastern China
Published in Annals of Human Biology, 2019
Meng Pan, Qin Ye, Xiao-Bin Ju, He Cui, Hui-Ying Zhou
In this study, we report the allele frequencies, forensic parameters, genetic distance and mutation rates of 19 autosomal STR loci in the Han population in Jiangsu, China. A total of 10,000 samples were collected for analysis, which is a very large sample size compared to previous studies. The genetic frequency and distribution characteristics in such a large sample could be obtained more objectively, and the results suggest that these 19 STR loci can provide highly informative polymorphic data for paternity testing, individual identification, and genetic population studies. No previous statistical analyses or studies have been carried out on the 7755 families that were used in the data collation and mutation rate analysis in the present study. The average mutation rate across all 19 loci was 1.4 × 10−3. The ratio of paternal-to-maternal mutation rates clearly suggests that mutations in the STR loci may be based more on paternal inheritance. The main six populations in this study maintained a relatively consistent trend in STR mutation rates. Finally, the results of the study will be recommended to local governments for the development of local population genetic frequency standards and their application to cumulative paternity index (CPI) calculations.