Maximum likelihood estimation of locus-specific mutation rates in Y-chromosome short tandem repeats

Motivation: Y-chromosome short tandem repeats (Y-STRs) are widely used for population studies, forensic purposes and, potentially, the study of disease, therefore knowledge of their mutation rate is valuable. Here we show a novel method for estimation of site-specific Y-STR mutation rates from partial phylogenetic information, via the maximum likelihood framework

Investigative leads in forensic genetics: Biogeographical Ancestry (BGA) and Kinship Analyses

The fundamental goal of forensic genetics is personal identification but it is common to obtain inconclusive results from both direct and indirect STR-profile comparisons. In such cases, it is necessary looking for alternative approaches to generate crucial forensic leads and identify unknown perpetrators. In this thesis, we propose alternative tools to predict BioGeographical Ancestry (BGA) and to identify males sharing the same Y-haplotype by utilizing multivariate techniques and Rapidly Mutating Y-chromosome short tandem repeats(RM Y-STRs), respectively. Concerning ethnic inference, we proposed novel statistical approaches (consisting in SLPCA, PLSDA and SVM methods) to group samples into BGA-classes, by testing both autosomal STRs (in African populations) and microhaplotypes (in U.S. populations). The predictive power of such statistics resulted extremely high; in fact, they enhance cluster separation providing misleading classifications for genetically mixed populations only. As to Y haplotype discrimination improvement, we proved the efficiency in individualization power of RM Y-STRs – reaching a total of 48 markers genotyped – in African populations characterized by high levels of endogamy, patrilinearity and population structuring. Together, these two innovative approaches converge in demonstrating they represent powerful tools to maximize the information inferable from biological evidence collected at the crime scene

A reference haplotype panel for genome-wide imputation of short tandem repeats.

Short tandem repeats (STRs) are involved in dozens of Mendelian disorders and have been implicated in complex traits. However, genotyping arrays used in genome-wide association studies focus on single nucleotide polymorphisms (SNPs) and do not readily allow identification of STR associations. We leverage next-generation sequencing (NGS) from 479 families to create a SNP + STR reference haplotype panel. Our panel enables imputing STR genotypes into SNP array data when NGS is not available for directly genotyping STRs. Imputed genotypes achieve mean concordance of 97% with observed genotypes in an external dataset compared to 71% expected under a naive model. Performance varies widely across STRs, with near perfect concordance at bi-allelic STRs vs. 70% at highly polymorphic repeats. Imputation increases power over individual SNPs to detect STR associations with gene expression. Imputing STRs into existing SNP datasets will enable the first large-scale STR association studies across a range of complex traits

Joint assembly and genetic mapping of the Atlantic horseshoe crab genome reveals ancient whole genome duplication

Horseshoe crabs are marine arthropods with a fossil record extending back approximately 450 million years. They exhibit remarkable morphological stability over their long evolutionary history, retaining a number of ancestral arthropod traits, and are often cited as examples of "living fossils." As arthropods, they belong to the Ecdysozoa}, an ancient super-phylum whose sequenced genomes (including insects and nematodes) have thus far shown more divergence from the ancestral pattern of eumetazoan genome organization than cnidarians, deuterostomes, and lophotrochozoans. However, much of ecdysozoan diversity remains unrepresented in comparative genomic analyses. Here we use a new strategy of combined de novo assembly and genetic mapping to examine the chromosome-scale genome organization of the Atlantic horseshoe crab Limulus polyphemus. We constructed a genetic linkage map of this 2.7 Gbp genome by sequencing the nuclear DNA of 34 wild-collected, full-sibling embryos and their parents at a mean redundancy of 1.1x per sample. The map includes 84,307 sequence markers and 5,775 candidate conserved protein coding genes. Comparison to other metazoan genomes shows that the L. polyphemus genome preserves ancestral bilaterian linkage groups, and that a common ancestor of modern horseshoe crabs underwent one or more ancient whole genome duplications (WGDs) ~ 300 MYA, followed by extensive chromosome fusion

Interpreting short tandem repeat variations in humans using mutational constraint

Identifying regions of the genome that are depleted of mutations can reveal potentially deleterious variants. Short tandem repeats (STRs), also known as microsatellites, are among the largest contributors of de novo mutations in humans. However, per-locus studies of STR mutations have been limited to highly ascertained panels of several dozen loci. Here, we harnessed bioinformatics tools and a novel analytical framework to estimate mutation parameters for each STR in the human genome by correlating STR genotypes with local sequence heterozygosity. We applied our method to obtain robust estimates of the impact of local sequence features on mutation parameters and used this to create a framework for measuring constraint at STRs by comparing observed vs. expected mutation rates. Constraint scores identified known pathogenic variants with early onset effects. Our metric will provide a valuable tool for prioritizing pathogenic STRs in medical genetics studies

Statistical issues in modelling the ancestry from Y-chromosome and surname data

A considerable industry has grown-up around genealogical inference from genetic testing, supplementing more traditional genealogical techniques but with very limited quantification of uncertainty. In many societies Y-chromosomes are co-inherited with surnames and as such passed down from father to son. This thesis seeks to explore what the correlation can say about ancestry. In particular it is concerned with estimation of the time to the most recent common paternal ancestor (TMRCA) for pairs of males who are not known to be directly related but share the same surname, based on the repeat number at short tandem repeat (STR) markers on their Y-chromosomes. We develop a model of TMRCA estimation based on the difference in repeat numbers in pairs of male haplotypes using a Bayesian framework and Markov-Chain Monte-Carlo techniques, such as adaptive Metropolis-Hastings algorithm. The model incorporates the process of STR discovery and the calibration of mutation rates, which can differ across STRs. In simulation studies, we find that the estimates of TMRCA are rather robust to the ascertainment process and the way in which it is modelled. However, they are affected by the site-specific mutation rates at the typed STRs. Indeed sequencing the fastest mutating STRs yields a lower error in the estimated TMRCA than random STRs. In the British context, we extend our model to include additional information such as the haplogroup status (as determined from single nucleotide polymorphisms, SNPs) of the pair of males, as well as the frequency and origin of the surname. In general, the effect of this is to reduce estimates of the TMRCA for pairs of males with an older TMRCA, typically outwith the period of surname establishment (about 500-700 years ago). In the genealogical context, incorporating surname frequency (within the prior distribution) results in lower estimates of TMRCA for pairs of males who appear to have diverged from a common male ancestor since the period of surname establishment. In addition, we include uncertainty in the years per generation conversion factor in our model

DNA identification by pedigree likelihood ratio accommodating population substructure and mutations

DNA typing is an important tool in missing-person identification, especially in mass-fatality disasters. Identification methods comparing a DNA profile from unidentified human remains with that of a direct (from the person) or indirect (for example, from a biological relative) reference sample and ranking the pairwise likelihood ratios (LR) is straightforward and well defined. However, for indirect comparison cases in which several members from a family can serve as reference samples, the full power of kinship analysis is not entirely exploited. Because biologically related family members are not genetically independent, more information and thus greater power can be attained by simultaneous use of all pedigree members in most cases, although distant relationships may reduce the power. In this study, an improvement was made on the method for missing-person identification for autosomal and lineage-based markers, by considering jointly the DNA profile data of all available family reference samples. The missing person is evaluated by a pedigree LR of the probability of DNA evidence under alternative hypotheses (for example, the missing person is unrelated or if they belong to this pedigree with a specified biological relationship) and can be ranked for all pedigrees within a database. Pedigree LRs are adjusted for population substructure according to the recommendations of the second National Research Council (NRCII) Report. A realistic mutation model was also incorporated to accommodate the possibility of false exclusion. The results show that the effect of mutation on the pedigree LR is moderate, but LRs can be significantly decreased by the effect of population substructure. Finally, Y chromosome and mitochondrial DNA were integrated into the analysis to increase the power of identification. A program titled MPKin was developed, combining the aforementioned features to facilitate genetic analysis for identifying missing persons. The computational complexity of the algorithms is explained, and several ways to reduce the complexity are introduced

Demographic Estimates from Y Chromosome Microsatellite Polymorphisms: Analysis of a Worldwide Sample

Polymorphisms in microsatellites on the human Y chromosome have been used to estimate important demographic parameters of human history. We compare two coalescent-based statistical methods that give estimates for a number of demographic parameters using the seven Y chromosome polymorphisms in the HGDP-CEPH Cell Line Panel, a collection of samples from 52 worldwide populations. The estimates for the time to the most recent common ancestor vary according to the method used and the assumptions about the prior distributions of model parameters, but are generally consistent with other global Y chromosome studies. We explore the sensitivity of these results to assumptions about the prior distributions and the evolutionary models themselves