SNPtotree-Resolving the Phylogeny of SNPs on Non-Recombining DNA.

Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures and infer migration patterns. Further, individuals can be assigned to the characterized populations, which is relevant in forensic genetics, genetic genealogy, and epidemiologic studies. However, there is currently no straightforward method to obtain such a variant hierarchy. Here, we introduce the software SNPtotree v1.0, which uniquely determines the hierarchical order of variants on non-recombining DNA without error-prone manual sorting. The algorithm uses pairwise variant comparisons to infer their relationships and integrates the combined information into a phylogenetic tree. Variants that have contradictory pairwise relationships or ambiguous positions in the tree are removed by the software. When benchmarked using two human Y-chromosomal massively parallel sequencing datasets, SNPtotree outperforms traditional methods in the accuracy of phylogenetic trees for sequencing data with high amounts of missing information. The phylogenetic trees of variants created using SNPtotree can be used to establish and maintain publicly available phylogeny databases to further explore genetic epidemiology and genealogy, as well as population and forensic genetics.

Pitfalls and challenges with population assignments of individuals from admixed populations: Applying Genogeographer on Brazilian individuals.

The assignment of individuals to a population can be of importance for the identification of mass disaster victims or criminal offenders in the field of forensic genetics. This assignment is based on biostatistical methods that process data of ancestry informative markers (AIMs), which are selected based on large allele frequency differences between the populations of interest. However, population assignments of individuals with an admixed genetic background are challenging. Admixed individuals are genetic mosaics of chromosomal segments from the parental populations, which may lead to ambiguous or no population assignment. This is problematic since admixture events are a substantial part of human history. In this study, we present challenges of interpreting the evidential weight of population assignments. We used Genogeographer for likelihood ratio (LR) calculations and Brazilians as examples of admixed individuals. Brazilians are a very heterogenous population representing a three-way admixture between Native Americans, Europeans, and Africans. Ancestry informative markers were typed in a total of 589 individuals from Brazil using the Precision ID Ancestry Panel. The Brazilians were assigned to six metapopulations (East Asia, Europe, Middle East, North Africa, South-Central Asia, Sub-Saharan Africa) defined in the Genogeographer software and LRs were calculated if the AIM profile was not an outlier in all metapopulations and simulated two-way (1:1) admixtures of the six metapopulations. Population assignments failed for 55% of the samples. These samples had significantly higher genetic contributions from East Asia, South-Central Asia and Sub-Saharan Africa, and significantly lower genetic contributions from Europe. Most of the individuals with population assignments were assigned to the metapopulations of Middle East (58%) or North Africa (36%), followed by Europe (4%), South-Central Asia (1%), and Sub-Saharan Africa (1%). For 8% of the samples, population assignments were only possible when assignments to simulated two-way (1:1) admixtures of the six metapopulations were considered. Most of these individuals were assigned to two-way admixtures of North Africa, South-Central Asia, or Sub-Saharan Africa. Relatively low median likelihood ratios (LRs<1000) were observed when comparing population likelihoods for Europe, Middle East, North Africa, South-Central Asia, or simulated 1:1 admixtures of these metapopulations. Comparisons including East Asian or Sub-Saharan African populations resulted in larger median LRs (LR>1010). The results suggested that the Precision ID Ancestry Panel provided too little information and that additional markers specifically selected for sub-continental differentiation may be required for accurate population assignment of admixed individuals. Furthermore, a Genogeographer database with additional populations including admixed populations would be advantageous for interpretation of admixed AIM profiles. It would likely increase the number of population assignments and illustrate alternatives to the most likely population, which would be valuable information for the case officer when writing the case report.

Testing the Ion AmpliSeq™ HID Y-SNP Research Panel v1 for performance and resolution in admixed South Americans of haplogroup Q.

Y haplogroups, defined by Y-SNPs, allow the reconstruction of the human Y chromosome genealogy, which is important for population, evolutionary and forensic genetics. In this study, Y-SNPs were typed and haplogroups inferred with the MPS Ion AmpliSeq™ HID Y-SNP Research Panel v1, as a high-throughput approach. Firstly, the performance of the panel was evaluated with different DNA input amounts, reagent volumes and cycle numbers. DNA-inputs from 0.5 to 1 ng generated the most balanced read depth. Combined with full reagent and 19 cycles, this offered the highest number of amplicons with a sequencing read depth of at least 20 reads. Secondly, the sub-haplogroups of 182 admixed South Americans and Greenlanders belonging to haplogroup Q were inferred and tested for potential improvement in resolution. Most samples were assigned to lineage Q-M3 with some samples assigned to lineages upstream (Q-M346, L56, L57; Q-L331, L53; Q-L54; Q-CTS11969, CTS11970) or parallel (Q-L330, L334; Q-Z780/M971) to Q-M3. Only one sample was assigned to a downstream lineage (Q-Z35615, Z35616). Most individuals of haplogroup Q with NAM ancestry could neither be distinguished from each other, nor from half of the Greenlandic samples. Typing additional, known SNPs within lineage Q-M3, Z19483 and SA05, increased the resolution of predicted haplogroups. The search for novel variants in the sequenced regions allowed the detection of 42 variants and the subdivision of lineage Q-M3 into new subclades. The variants found in six of these subclades were exclusive to certain South American countries. In light of the limited differentiation of haplogroup Q samples, the additional information on known or novel SNPs disclosed in this study when using MPS Ion AmpliSeq™ HID Y-SNP Research Panel v1 should be included in the Yleaf software, to increase the differentiation of lineage Q-M3.