Genetic population study of Y-chromosome markers in Benin and Ivory Coast ethnic groups

The Qatari population's genetic structure and gene flow as revealed by the Y chromosome

The Y-chromosome has been widely used in forensic genetic applications and human population genetic studies due to its uniparental origins. A large database on the Qatari population was created for comparison with other databases from the Arabian Peninsula, the Middle East, and Africa. We provide a study of 23 Y-STR loci included in PowerPlex Y23 (Promega, USA) that were genotyped to produce haplotypes in 379 unrelated males from Qatar, a country at the crossroads of migration patterns. Overall, the most polymorphic locus provided by the Promega kit was DYS458, with a genetic diversity value of 0.85 and a haplotype diversity of 0.998924. Athey's Haplogroup Predictor tool was used to predict haplogroups from Y-STR haplotypes in the Qatari population. In a median-joining network, the haplogroup J1 predominance (49%) in Qatar generated a star-like expansion cluster. The graph of population Q-matrix was developed using Y-STR data from 38 Middle Eastern and 97 African populations (11,305 individuals), and it demonstrated a stronger sub-grouping of countries within each ethnic group and showed the effect of Arabs on the indigenous Berbers of North Africa. The estimated migration rate between the Qatari and other Arabian populations was inferred using Bayesian coalescence theory in the Migrate-n program. According to the Gene Flow study, the main migration route was from Yemen to Kuwait through Qatar. Our research, using the PowerPlex Y23 database, shows the importance of gene diversity, as well as regional and social structuring, in determining the utility of demographic and forensic databases.

Population data and genetic structure analysis based on 29 Y-STR loci among the ethnolinguistic groups in Burkina Faso

Burkina Faso (BF) is a landlocked Sahelian country located in the middle of West Africa. Sixty-three local languages are spoken in BF. Despite this high diversity, the BF population remains poorly investigated, and updated forensic parameters with a large number of Y chromosome short tandem repeats (Y-STRs) are still missing. Herein, 447 DNA samples were typed for a cocktail of 29 Y-STR loci. None of these 447 individuals in total shared a common haplotype. The overall Y-STR haplotypes were successfully uploaded online on the Y-STR Haplotype Reference Database (YHRD) with the accession numbers YA004690 and YA004691. The main haplotype diversity was 0.9999999965, which is much higher than that obtained with 12 Y-STRs in a previous study. Haploid Match Probability for the whole dataset was 0.002237. The phylogenetic analysis of 24 ethnic groups of BF shows that the ethnic group named BISSA is closer to Gur speakers than Mande speakers, where they belong. In addition, genetic structure analysis of 49 African subpopulations sheds light on the fact that geographic proximity turns out to be one of the best predictors of genetic affinity between populations.

Predicting haplogroups using a versatile machine learning program (PredYMaLe) on a new mutationally balanced 32 Y-STR multiplex (CombYplex): Unlocking the full potential of the human STR mutation rate spectrum to estimate forensic parameters

We developed a new mutationally well-balanced 32 Y-STR multiplex (CombYplex) together with a machine learning (ML) program PredYMaLe to assess the impact of STR mutability on haplogourp prediction, while respecting forensic community criteria (high DC/HD). We designed CombYplex around two sub-panels M1 and M2 characterized by average and high-mutation STR panels. Using these two sub-panels, we tested how our program PredYmale reacts to mutability when considering basal branches and, moving down, terminal branches. We tested first the discrimination capacity of CombYplex on 996 human samples using various forensic and statistical parameters and showed that its resolution is sufficient to separate haplogroup classes. In parallel, PredYMaLe was designed and used to test whether a ML approach can predict haplogroup classes from Y-STR profiles. Applied to our kit, SVM and Random Forest classifiers perform very well (average 97 %), better than Neural Network (average 91 %) and Bayesian methods (< 90 %). We observe heterogeneity in haplogroup assignation accuracy among classes, with most haplogroups having high prediction scores (99-100 %) and two (E1b1b and G) having lower scores (67 %). The small sample sizes of these classes explain the high tendency to misclassify the Y-profiles of these haplogroups; results were measurably improved as soon as more training data were added. We provide evidence that our ML approach is a robust method to accurately predict haplogroups when it is combined with a sufficient number of markers, well-balanced mutation rate Y-STR panels, and large ML training sets. Further research on confounding factors (such as CNV-STR or gene conversion) and ideal STR panels in regard to the branches analysed can be developed to help classifiers further optimize prediction scores.

Population data of 23 Y chromosome STR loci for the five major human subpopulations of Ghana

In this study, 268 samples for unrelated males belonging to the five major human subpopulation groups in Ghana (Akan, Ewe, Mole-Dagbon, Ga-Dangme and Guang) were genetically characterised for 23 Y chromosome short tandem repeat (STR) loci using the Powerplex® Y23 STR kit. A total of 263 complete haplotypes were recorded of which 258 were unique. The haplotype diversity, discriminating capacity and match probability for the pooled population data were 0.9998, 0.9627 and 0.0039, respectively. The pairwise genetic distance (R_ST) for the Ghanaian datasets and other reference populations deposited in the Y-STR Haplotype Reference Database (YHRD) were estimated and mapped using multidimensional scaling (MDS) plot. The Guang and Ewe were significantly different from the Akan, Mole-Dagbon and Ga-Dangme. However, the five Ghanaian datasets were all plotted close together with other African populations in the MDS data mapping.

Reconstructing an African haploid genome from the 18th century

A genome is a mosaic of chromosome fragments from ancestors who existed some arbitrary number of generations earlier. Here, we reconstruct the genome of Hans Jonatan (HJ), born in the Caribbean in 1784 to an enslaved African mother and European father. HJ migrated to Iceland in 1802, married and had two children. We genotyped 182 of his 788 descendants using single-nucleotide polymorphism (SNP) chips and whole-genome sequenced (WGS) 20 of them. Using these data, we reconstructed 38% of HJ's maternal genome and inferred that his mother was from the region spanned by Benin, Nigeria and Cameroon.