Forensic Efficiency Parameters for the 15 STR Loci in the Population of the Island of Cres (Croatia)

Forensic parameters based on 15 AmpFlSTR Identifiler short tandem repeat (STR) loci (D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, VWA, TPOX, D18S51, D5S818 and FGA) were evaluated in the sample of 122 unrelated, autochthonous, adult individuals from the Island of Cres (Croatia). PCR amplification was performed with the AmpFlSTR Identifiler PCR Amplification Kit and the amplified products were separated and detected using the ABI 3130 DNA genetic analyzer. The agreement with Hardy Weinberg Equilibrium (HWE) was confirmed for all loci (p>0.05). The combined power of discrimination (PD) and the combined power of exclusion (PE) for the 15 tested STR loci were 0.99999999999999997988728679 and 0.999997397, respectively. According to the presented data, D18S51 proved to be the most informative marker followed by markers D2S1338 and D21S11. Interpopulation comparisons in allele frequencies with other East Adriatic Islands revealed significant differences for all analyzed population pairs ranging from 4 loci (Cres vs. Hvar) to 1 locus (Cres vs. Krk). Furthermore, allele frequencies comparisons of Cres and Croatian mainland revealed the lack of statistically significant differences at all studied loci. The results of the current study indicate that the examined fifteen STR loci are useful genetic markers for individual identification and paternity testing in Croatian population from the Island of Cres

Allele Frequencies for 15 Short Tandem Repeat Loci in Representative Sample of Croatian Population

Aim To study the distribution of allele frequencies of 15 short tandem repeat (STR) loci in a representative sample of Croatian population. Methods A total of 195 unrelated Caucasian individuals born in Croatia, from 14 counties and the City of Zagreb, were sampled for the analysis. All the tested individuals were voluntary donors. Buccal swab was used as the DNA source. AmpFlSTR® Identifiler® was applied to simultaneously amplify 15 STR loci. Total reaction volume was 12.5 μL. The PCR amplification was carried out in PE Gene Amp PCR System Thermal Cycler. Electrophoresis of the amplification products was preformed on an ABI PRISM 3130 Genetic Analyzer. After PCR amplification and separation by electrophoresis, raw data were compiled, analyzed, and numerical allele designations of the profiles were obtained. Deviation from Hardy-Weinberg equilibrium, observed and expected heterozygosity, power of discrimination, and power of exclusion were calculated. Bonferroni’s correction was used before each comparative analysis. Results We compared Croatian data with those obtained from geographically neighboring European populations. The significant difference (at P<0.01) in allele frequencies was recorded only between Croatian and Slovenian populations for vWA locus. There was no significant deviation from Hardy-Weinberg equilibrium for all the observed loci. Conclusion Obtained population data concurred with the expected “STR data frame” for this part of Europe

Identification of human remains from the Second World War mass graves uncovered in Bosnia and Herzegovina

Aim To present the results obtained in the identification of human remains from World War II found in two mass graves in Ljubuški, Bosnia and Herzegovina. Methods Samples from 10 skeletal remains were collected. Teeth and femoral fragments were collected from 9 skeletons and only a femoral fragment from 1 skeleton. DNA was isolated from bone and teeth samples using an optimized phenol/chloroform DNA extraction procedure. All samples required a pre-extraction decalcification with EDTA and additional post-extraction DNA purification using filter columns. Additionally, DNA from 12 reference samples (buccal swabs from potential living relatives) was extracted using the Qiagen DNA extraction method. QuantifilerTM Human DNA Quantification Kit was used for DNA quantification. PowerPlex ESI kit was used to simultaneously amplify 15 autosomal short tandem repeat (STR) loci, and PowerPlex Y23 was used to amplify 23 Y chromosomal STR loci. Matching probabilities were estimated using a standard statistical approach. Results A total of 10 samples were processed, 9 teeth and 1 femoral fragment. Nine of 10 samples were profiled using autosomal STR loci, which resulted in useful DNA profiles for 9 skeletal remains. A comparison of established victims’ profiles against a reference sample database yielded 6 positive identifications. Conclusion DNA analysis may efficiently contribute to the identification of remains even seven decades after the end of the World War II. The significant percentage of positively identified remains (60%), even when the number of the examined possible living relatives was relatively small (only 12), proved the importance of cooperation with the members of the local community, who helped to identify the closest missing persons’ relatives and collect referent samples from them

Haplogroup Prediction Using Y-Chromosomal Short Tandem Repeats in the General Population of Bosnia and Herzegovina

Human Y-chromosomal haplogroups are an important tool used in population genetics and forensic genetics. A conventional method used for Y haplogroup assignment is based on a set of Y-single nucleotide polymorphism (SNP) markers deployed, which exploits the low mutation rate nature of these markers. Y chromosome haplogroups can be successfully predicted from Y-short tandem repeat (STR) markers using different software packages, and this method gained much attention recently due to its labor-, time-, and cost-effectiveness. The present study was based on the analysis of a total of 480 adult male buccal swab samples collected from different regions of Bosnia and Herzegovina. Y haplogroup prediction was performed using Whit Athey’s Haplogroup Predictor, based on haplotype data on 23 Y-STR markers contained within the PowerPlex® Y23 kit. The results revealed the existence of 14 different haplogroups, with I2a, R1a, and E1b1b being the most prevalent with frequencies of 43.13, 14.79, and 14.58%, respectively. Compared to the previously published studies on Bosnian-Herzegovinian population based on Y-SNP and Y-STR data, this study represents an upgrade of molecular genetic data with a significantly larger number of samples, thus offering more accurate results and higher probability of detecting rare haplogroups

Genomic analyses inform on migration events during the peopling of Eurasia.

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.Support was provided by: Estonian Research Infrastructure Roadmap grant no 3.2.0304.11-0312; Australian Research Council Discovery grants (DP110102635 and DP140101405) (D.M.L., M.W. and E.W.); Danish National Research Foundation; the Lundbeck Foundation and KU2016 (E.W.); ERC Starting Investigator grant (FP7 - 261213) (T.K.); Estonian Research Council grant PUT766 (G.C. and M.K.); EU European Regional Development Fund through the Centre of Excellence in Genomics to Estonian Biocentre (R.V.; M.Me. and A.Me.), and Centre of Excellence for Genomics and Translational Medicine Project No. 2014-2020.4.01.15-0012 to EGC of UT (A.Me.) and EBC (M.Me.); Estonian Institutional Research grant IUT24-1 (L.S., M.J., A.K., B.Y., K.T., C.B.M., Le.S., H.Sa., S.L., D.M.B., E.M., R.V., G.H., M.K., G.C., T.K. and M.Me.) and IUT20-60 (A.Me.); French Ministry of Foreign and European Affairs and French ANR grant number ANR-14-CE31-0013-01 (F.-X.R.); Gates Cambridge Trust Funding (E.J.); ICG SB RAS (No. VI.58.1.1) (D.V.L.); Leverhulme Programme grant no. RP2011-R-045 (A.B.M., P.G. and M.G.T.); Ministry of Education and Science of Russia; Project 6.656.2014/K (S.A.F.); NEFREX grant funded by the European Union (People Marie Curie Actions; International Research Staff Exchange Scheme; call FP7-PEOPLE-2012-IRSES-number 318979) (M.Me., G.H. and M.K.); NIH grants 5DP1ES022577 05, 1R01DK104339-01, and 1R01GM113657-01 (S.Tis.); Russian Foundation for Basic Research (grant N 14-06-00180a) (M.G.); Russian Foundation for Basic Research; grant 16-04-00890 (O.B. and E.B); Russian Science Foundation grant 14-14-00827 (O.B.); The Russian Foundation for Basic Research (14-04-00725-a), The Russian Humanitarian Scientific Foundation (13-11-02014) and the Program of the Basic Research of the RAS Presidium “Biological diversity” (E.K.K.); Wellcome Trust and Royal Society grant WT104125AIA & the Bristol Advanced Computing Research Centre (http://www.bris.ac.uk/acrc/) (D.J.L.); Wellcome Trust grant 098051 (Q.A.; C.T.-S. and Y.X.); Wellcome Trust Senior Research Fellowship grant 100719/Z/12/Z (M.G.T.); Young Explorers Grant from the National Geographic Society (8900-11) (C.A.E.); ERC Consolidator Grant 647787 ‘LocalAdaptatio’ (A.Ma.); Program of the RAS Presidium “Basic research for the development of the Russian Arctic” (B.M.); Russian Foundation for Basic Research grant 16-06-00303 (E.B.); a Rutherford Fellowship (RDF-10-MAU-001) from the Royal Society of New Zealand (M.P.C.)

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype–phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine

Genetic sub-structuring of Croatian island populations in the Southeastern European context: a meta-analysis

Aim To use the method of meta-analysis to assess the influence of island population isolation on the sub-structuring of the Croatian population, as well as the influence of regional population groups on the sub-structuring of the Southeastern European population with regard to basic population genetic statistical parameters calculated by using STR locus analysis. Methods Bio-statistical analyses were performed for 2877 unrelated participants of both sexes from Southeastern Europe. Nine autosomal STR loci (D3S1358, vWA, FGA, TH01, TPOX, CSF1PO, D5S818, D13S317, and D7S82) were analyzed by using standard F-statistics and population structure analysis (Structure software). Results Genetic differentiation of Croatian subpopulations assessed with the FST method was higher at the level of the Croatian population (0.005) than at the level of Southeastern Europe (0.002). The island of Vis showed the most pronounced separation in the Croatian population, and Albanians from Kosovo in the population of Southeast Europe, followed by Croatia, Bosnia and Herzegovina, and Hungary. Conclusion The higher structure of Croatian subpopulations in relation to Southeastern Europe suggest a certain degree of genetic isolation, most likely due to the influence of endogamy within rural island populations

Allele Frequencies for 15 Short Tandem Repeat Loci in Representative Sample of Croatian Population

Aim To study the distribution of allele frequencies of 15 short tandem repeat (STR) loci in a representative sample of Croatian population. Methods A total of 195 unrelated Caucasian individuals born in Croatia, from 14 counties and the City of Zagreb, were sampled for the analysis. All the tested individuals were voluntary donors. Buccal swab was used as the DNA source. AmpFlSTR® Identifiler® was applied to simultaneously amplify 15 STR loci. Total reaction volume was 12.5 μL. The PCR amplification was carried out in PE Gene Amp PCR System Thermal Cycler. Electrophoresis of the amplification products was preformed on an ABI PRISM 3130 Genetic Analyzer. After PCR amplification and separation by electrophoresis, raw data were compiled, analyzed, and numerical allele designations of the profiles were obtained. Deviation from Hardy-Weinberg equilibrium, observed and expected heterozygosity, power of discrimination, and power of exclusion were calculated. Bonferroni’s correction was used before each comparative analysis. Results We compared Croatian data with those obtained from geographically neighboring European populations. The significant difference (at P<0.01) in allele frequencies was recorded only between Croatian and Slovenian populations for vWA locus. There was no significant deviation from Hardy-Weinberg equilibrium for all the observed loci. Conclusion Obtained population data concurred with the expected “STR data frame” for this part of Europe

Influence of genetic substructuring of statistical forensic parameters on genetic short tandem repeat markers in the populations of Southeastern Europe

Aim To investigate the influence of specific intrapopula - tion genetic structures on interpopulation relationships. Special focus was the influence of island population isola - tion on the substructuring of the Croatian population, and the influence of regional population groups on the sub - structuring of Southeast European populations. Methods Autosomal short tandem repeat (STR) loci were analyzed by using four forensic parameters: matching probability (PM), power of discrimination (PD), power of exclusion (PE), and polymorphic information content (PIC) on a sample of 2877 unrelated participants of both sexes. A sample set comprising 590 participants was analyzed for the first time, and 2287 participants were included from previous studies. The analysis was performed with Power - Stats v. 1.2. Results The analysis of forensic parameters for all nine loci in the Croatian subpopulations showed the largest devia - tions in the populations of the islands of Korčula and Hvar. The smallest deviations were found in the mainland popu - lation. As for Southeast European populations, the largest deviations were found in the population of North Mace - donia, followed by Romania, Albanians from Kosovo, and Montenegro, while the smallest deviations were found in the population of Hungary. Conclusion The comparison of forensic parameters be - tween different subpopulations of Croatia and Southeast Europe indicates that the isolation of individual Croatian subpopulations and rare alleles in their gene pool affect the values of forensic parameters. Specific features of (sub) populations should be taken into account for appropriate sampling of the total population when creating a DNA da - tabase of STR markers