The large single nucleotide polymorphism (SNP) typing projects have provided an invaluable data resource for human population geneticists. Almost all of the available SNP loci, however, have been identified through a SNP discovery protocol that will influence the allelic distributions in the sampled loci. Standard methods for population genetic analysis based on the available SNP data will, therefore, be biased. This paper discusses the effect of this ascertainment bias on allelic distributions and on methods for quantifying linkage disequilibrium and estimating demographic parameters. Several recently developed methods for correcting for the ascertainment bias will also be discussed.

1. The number of individuals in a random sample with close relatives in the sample is a quantity of interest when designing Genome Wide Association Studies (GWAS) and other cohort based genetic, and non-genetic, studies. In this paper, we develop expressions for the distribution and expectation of the number of p -th cousins in a sample from a population of size N under two diploid Wright-Fisher models. We also develop simple asymptotic expressions for large values of N . For example, the expected proportion of individuals with at least one p -th cousin in a sample of K individuals, for a diploid dioecious Wright-Fisher model, is approximately 1 − e −(2 2 p −1 ) K/N . Our results show that a substantial fraction of individuals in the sample will have at least a second cousin if the sampling fraction ( K/N ) is on the order of 10 −2 . This confirms that, for large cohort samples, relatedness among individuals cannot easily be ignored.

Background

Single cell whole genome tumor sequencing can yield novel insights into the evolutionary history of somatic copy number alterations. Existing single cell copy number calling methods do not explicitly model the shared evolutionary process of multiple cells, and generally analyze cells independently. Additionally, existing methods for estimating tumor cell phylogenies using copy number profiles are sensitive to profile estimation errors.

Results

We present SCONCE2, a method for jointly calling copy number alterations and estimating pairwise distances for single cell sequencing data. Using simulations, we show that SCONCE2 has higher accuracy in copy number calling and phylogeny estimation than competing methods. We apply SCONCE2 to previously published single cell sequencing data to illustrate the utility of the method.

Conclusions

SCONCE2 jointly estimates copy number profiles and a distance metric for inferring tumor phylogenies in single cell whole genome tumor sequencing across multiple cells, enabling deeper understandings of tumor evolution.

About 2% of human genetic polymorphisms have been hypothesized to arise via multinucleotide mutations (MNMs), complex events that generate SNPs at multiple sites in a single generation. MNMs have the potential to accelerate the pace at which single genes evolve and to confound studies of demography and selection that assume all SNPs arise independently. In this paper, we examine clustered mutations that are segregating in a set of 1092 human genomes, demonstrating that the signature of MNM becomes enriched as large numbers of individuals are sampled. We estimate the percentage of linked SNP pairs that were generated by simultaneous mutation as a function of the distance between affected sites and show that MNMs exhibit a high percentage of transversions relative to transitions, findings that are reproducible in data from multiple sequencing platforms and cannot be attributed to sequencing error. Among tandem mutations that occur simultaneously at adjacent sites, we find an especially skewed distribution of ancestral and derived alleles, with GC → AA, GA → TT, and their reverse complements making up 27% of the total. These mutations have been previously shown to dominate the spectrum of the error-prone polymerase Pol ζ, suggesting that low-fidelity DNA replication by Pol ζ is at least partly responsible for the MNMs that are segregating in the human population. We develop statistical estimates of MNM prevalence that can be used to correct phylogenetic and population genetic inferences for the presence of complex mutations.

The distribution of admixture tract lengths has received considerable attention, in part because it can be used to infer the timing of past gene flow events between populations. It is commonly assumed that these lengths can be modeled as independently and identically distributed (iid) exponential random variables. This assumption is fundamental for many popular methods that analyze admixture using hidden Markov models. We compare the expected distribution of admixture tract lengths under a number of population-genetic models to the distribution predicted by the Wright-Fisher model with recombination. We show that under the latter model, the assumption of iid exponential tract lengths does not hold for recent or for ancient admixture events and that relying on this assumption can lead to false positives when inferring the number of admixture events. To further investigate the tract-length distribution, we develop a dyadic interval-based stochastic process for generating admixture tracts. This representation is useful for analyzing admixture tract-length distributions for populations with recent admixture, a scenario in which existing models perform poorly.

We use the genotyping and death register information of 409,693 individuals of British ancestry to investigate fitness effects of the CCR5-∆32 mutation. We estimate a 21% increase in the all-cause mortality rate in individuals who are homozygous for the ∆32 allele. A deleterious effect of the ∆32/∆32 mutation is also independently supported by a significant deviation from the Hardy-Weinberg equilibrium (HWE) due to a deficiency of ∆32/∆32 individuals at the time of recruitment.

The distribution of admixture tract lengths has received considerable attention, in part because it can be used to infer the timing of past gene flow events between populations. It is commonly assumed that these lengths can be modeled as independently and identically distributed (iid) exponential random variables. This assumption is fundamental for many popular methods that analyze admixture using hidden Markov models. We compare the expected distribution of admixture tract lengths under a number of population-genetic models to the distribution predicted by the Wright-Fisher model with recombination. We show that under the latter model, the assumption of iid exponential tract lengths does not hold for recent or for ancient admixture events and that relying on this assumption can lead to false positives when inferring the number of admixture events. To further investigate the tract-length distribution, we develop a dyadic interval-based stochastic process for generating admixture tracts. This representation is useful for analyzing admixture tract-length distributions for populations with recent admixture, a scenario in which existing models perform poorly.

Approximately 2-4% of genetic material in human populations outside Africa is derived from Neanderthals who interbred with anatomically modern humans. Recent studies have shown that this Neanderthal DNA is depleted around functional genomic regions; this has been suggested to be a consequence of harmful epistatic interactions between human and Neanderthal alleles. However, using published estimates of Neanderthal inbreeding and the distribution of mutational fitness effects, we infer that Neanderthals had at least 40% lower fitness than humans on average; this increased load predicts the reduction in Neanderthal introgression around genes without the need to invoke epistasis. We also predict a residual Neanderthal mutational load in non-Africans, leading to a fitness reduction of at least 0.5%. This effect of Neanderthal admixture has been left out of previous debate on mutation load differences between Africans and non-Africans. We also show that if many deleterious mutations are recessive, the Neanderthal admixture fraction could increase over time due to the protective effect of Neanderthal haplotypes against deleterious alleles that arose recently in the human population. This might partially explain why so many organisms retain gene flow from other species and appear to derive adaptive benefits from introgression.

The multi-species coalescent (MSC) provides a theoretical foundation for modern phylogenetics and comparative population genetics. Its theoretical properties have been heavily studied but there are still aspects of the MSC that are largely unknown, including the covariances in pairwise coalescence times, which are fundamental for understanding the properties of statistics that combine data from multiple species, such as the fixation index (F_ST). The major contribution of this study is the derivation and implementation of exact expressions for the covariances of pairwise coalescence times under phylogenetic models with piecewise constant changes in population size, assuming no gene flow after species divergence. We use these expressions to derive the variance in average pairwise differences within and between populations. We then derive approximations for the expectation and bias of a sequence-based estimator of F_ST, a commonly used genetic measurement of population differentiation, when it is applied to a non-recombining region of the genome. We show that the estimator of F_ST is generally biased downward. A freely available software package is provided, STCov, to calculate the mean, variances and covariances in coalescence times presented here under user-defined piecewise-constant species trees. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.