Ilan Gronau

Bayesian inference of ancient human demography from individual genome sequences

Whole-genome sequences provide a rich source of information about human evolution. Here we describe an effort to estimate key evolutionary parameters based on the whole-genome sequences of six individuals from diverse human populations. We used a Bayesian, coalescent-based approach to obtain information about ancestral population sizes, divergence times and migration rates from inferred genealogies at many neutrally evolving loci across the genome. We introduce new methods for accommodating gene flow between populations and integrating over possible phasings of diploid genotypes. We also describe a custom pipeline for genotype inference to mitigate biases from heterogeneous sequencing technologies and coverage levels. Our analysis indicates that the San population of southern Africa diverged from other human populations approximately 108–157 thousand years ago, that Eurasians diverged from an ancestral African population 38–64 thousand years ago, and that the effective population size of the ancestors of all modern humans was ∼9,000.

Genome Sequencing Highlights the Dynamic Early History of Dogs

To identify genetic changes underlying dog domestication and reconstruct their early evolutionary history, we generated high-quality genome sequences from three gray wolves, one from each of the three putative centers of dog domestication, two basal dog lineages (Basenji and Dingo) and a golden jackal as an outgroup. Analysis of these sequences supports a demographic model in which dogs and wolves diverged through a dynamic process involving population bottlenecks in both lineages and post-divergence gene flow. In dogs, the domestication bottleneck involved at least a 16-fold reduction in population size, a much more severe bottleneck than estimated previously. A sharp bottleneck in wolves occurred soon after their divergence from dogs, implying that the pool of diversity from which dogs arose was substantially larger than represented by modern wolf populations. We narrow the plausible range for the date of initial dog domestication to an interval spanning 11–16 thousand years ago, predating the rise of agriculture. In light of this finding, we expand upon previous work regarding the increase in copy number of the amylase gene (AMY2B) in dogs, which is believed to have aided digestion of starch in agricultural refuse. We find standing variation for amylase copy number variation in wolves and little or no copy number increase in the Dingo and Husky lineages. In conjunction with the estimated timing of dog origins, these results provide additional support to archaeological finds, suggesting the earliest dogs arose alongside hunter-gathers rather than agriculturists. Regarding the geographic origin of dogs, we find that, surprisingly, none of the extant wolf lineages from putative domestication centers is more closely related to dogs, and, instead, the sampled wolves form a sister monophyletic clade. This result, in combination with dog-wolf admixture during the process of domestication, suggests that a re-evaluation of past hypotheses regarding dog origins is necessary.

Ancient gene flow from early modern humans into Eastern Neanderthals

It has been shown that Neanderthals contributed genetically to modern humans outside Africa 47,000–65,000 years ago. Here we analyse the genomes of a Neanderthal and a Denisovan from the Altai Mountains in Siberia together with the sequences of chromosome 21 of two Neanderthals from Spain and Croatia. We find that a population that diverged early from other modern humans in Africa contributed genetically to the ancestors of Neanderthals from the Altai Mountains roughly 100,000 years ago. By contrast, we do not detect such a genetic contribution in the Denisovan or the two European Neanderthals. We conclude that in addition to later interbreeding events, the ancestors of Neanderthals from the Altai Mountains and early modern humans met and interbred, possibly in the Near East, many thousands of years earlier than previously thought.

Genome-wide inference of ancestral recombination graphs

The complex correlation structure of a collection of orthologous DNA sequences is uniquely captured by the “ancestral recombination graph” (ARG), a complete record of coalescence and recombination events in the history of the sample. However, existing methods for ARG inference are computationally intensive, highly approximate, or limited to small numbers of sequences, and, as a consequence, explicit ARG inference is rarely used in applied population genomics. Here, we introduce a new algorithm for ARG inference that is efficient enough to apply to dozens of complete mammalian genomes. The key idea of our approach is to sample an ARG of chromosomes conditional on an ARG of chromosomes, an operation we call “threading.” Using techniques based on hidden Markov models, we can perform this threading operation exactly, up to the assumptions of the sequentially Markov coalescent and a discretization of time. An extension allows for threading of subtrees instead of individual sequences. Repeated application of these threading operations results in highly efficient Markov chain Monte Carlo samplers for ARGs. We have implemented these methods in a computer program called ARGweaver. Experiments with simulated data indicate that ARGweaver converges rapidly to the posterior distribution over ARGs and is effective in recovering various features of the ARG for dozens of sequences generated under realistic parameters for human populations. In applications of ARGweaver to 54 human genome sequences from Complete Genomics, we find clear signatures of natural selection, including regions of unusually ancient ancestry associated with balancing selection and reductions in allele age in sites under directional selection. The patterns we observe near protein-coding genes are consistent with a primary influence from background selection rather than hitchhiking, although we cannot rule out a contribution from recurrent selective sweeps.

Genome-wide inference of natural selection on human transcription factor binding sites

For decades, it has been hypothesized that gene regulation has had a central role in human evolution, yet much remains unknown about the genome-wide impact of regulatory mutations. Here we use whole-genome sequences and genome-wide chromatin immunoprecipitation and sequencing data to demonstrate that natural selection has profoundly influenced human transcription factor binding sites since the divergence of humans from chimpanzees 4–6 million years ago. Our analysis uses a new probabilistic method, called INSIGHT, for measuring the influence of selection on collections of short, interspersed noncoding elements. We find that, on average, transcription factor binding sites have experienced somewhat weaker selection than protein-coding genes. However, the binding sites of several transcription factors show clear evidence of adaptation. Several measures of selection are strongly correlated with predicted binding affinity. Overall, regulatory elements seem to contribute substantially to both adaptive substitutions and deleterious polymorphisms with key implications for human evolution and disease.

Recursive construction of perfect DNA molecules from imperfect oligonucleotides.

Making faultless complex objects from potentially faulty building blocks is a fundamental challenge in computer engineering, nanotechnology and synthetic biology. Here, we show for the first time how recursion can be used to address this challenge and demonstrate a recursive procedure that constructs error‐free DNA molecules and their libraries from error‐prone oligonucleotides. Divide and Conquer (D&C), the quintessential recursive problem‐solving technique, is applied in silico to divide the target DNA sequence into overlapping oligonucleotides short enough to be synthesized directly, albeit with errors; error‐prone oligonucleotides are recursively combined in vitro, forming error‐prone DNA molecules; error‐free fragments of these molecules are then identified, extracted and used as new, typically longer and more accurate, inputs to another iteration of the recursive construction procedure; the entire process repeats until an error‐free target molecule is formed. Our recursive construction procedure surpasses existing methods for de novo DNA synthesis in speed, precision, amenability to automation, ease of combining synthetic and natural DNA fragments, and ability to construct designer DNA libraries. It thus provides a novel and robust foundation for the design and construction of synthetic biological molecules and organisms.

Worldwide patterns of genomic variation and admixture in gray wolves

The gray wolf (Canis lupus) is a widely distributed top predator and ancestor of the domestic dog. To address questions about wolf relationships to each other and dogs, we assembled and analyzed a data set of 34 canine genomes. The divergence between New and Old World wolves is the earliest branching event and is followed by the divergence of Old World wolves and dogs, confirming that the dog was domesticated in the Old World. However, no single wolf population is more closely related to dogs, supporting the hypothesis that dogs were derived from an extinct wolf population. All extant wolves have a surprisingly recent common ancestry and experienced a dramatic population decline beginning at least ∼30 thousand years ago (kya). We suggest this crisis was related to the colonization of Eurasia by modern human hunter-gatherers, who competed with wolves for limited prey but also domesticated them, leading to a compensatory population expansion of dogs. We found extensive admixture between dogs and wolves, with up to 25% of Eurasian wolf genomes showing signs of dog ancestry. Dogs have influenced the recent history of wolves through admixture and vice versa, potentially enhancing adaptation. Simple scenarios of dog domestication are confounded by admixture, and studies that do not take admixture into account with specific demographic models are problematic.

Whole-genome sequence analysis shows that two endemic species of North American wolf are admixtures of the coyote and gray wolf

Genome admixture in two endemic North American wolf species. Protection of populations comprising admixed genomes is a challenge under the Endangered Species Act (ESA), which is regarded as the most powerful species protection legislation ever passed in the United States but lacks specific provisions for hybrids. The eastern wolf is a newly recognized wolf-like species that is highly admixed and inhabits the Great Lakes and eastern United States, a region previously thought to be included in the geographic range of only the gray wolf. The U.S. Fish and Wildlife Service has argued that the presence of the eastern wolf, rather than the gray wolf, in this area is grounds for removing ESA protection (delisting) from the gray wolf across its geographic range. In contrast, the red wolf from the southeastern United States was one of the first species protected under the ESA and was protected despite admixture with coyotes. We use whole-genome sequence data to demonstrate a lack of unique ancestry in eastern and red wolves that would not be expected if they represented long divergent North American lineages. These results suggest that arguments for delisting the gray wolf are not valid. Our findings demonstrate how a strict designation of a species under the ESA that does not consider admixture can threaten the protection of endangered entities. We argue for a more balanced approach that focuses on the ecological context of admixture and allows for evolutionary processes to potentially restore historical patterns of genetic variation.

Distinguishing Noise from Signal in Patterns of Genomic Divergence in a Highly Polymorphic Avian Radiation

Recently diverged taxa provide the opportunity to search for the genetic basis of the phenotypes that distinguish them. Genomic scans aim to identify loci that are diverged with respect to an otherwise weakly differentiated genetic background. These loci are candidates for being past targets of selection because they behave differently from the rest of the genome that has either not yet differentiated or that may cross species barriers through introgressive hybridization. Here we use a reduced‐representation genomic approach to explore divergence among six species of southern capuchino seedeaters, a group of recently radiated sympatric passerine birds in the genus Sporophila. For the first time in these taxa, we discovered a small proportion of markers that appeared differentiated among species. However, when assessing the significance of these signatures of divergence, we found that similar patterns can also be recovered from random grouping of individuals representing different species. A detailed demographic inference indicates that genetic differences among Sporophila species could be the consequence of neutral processes, which include a very large ancestral effective population size that accentuates the effects of incomplete lineage sorting. As these neutral phenomena can generate genomic scan patterns that mimic those of markers involved in speciation and phenotypic differentiation, they highlight the need for caution when ascertaining and interpreting differentiated markers between species, especially when large numbers of markers are surveyed. Our study provides new insights into the demography of the southern capuchino radiation and proposes controls to distinguish signal from noise in similar genomic scans.

Inference of Natural Selection from Interspersed Genomic Elements Based on Polymorphism and Divergence

Complete genome sequences contain valuable information about natural selection, but this information is difficult to access for short, widely scattered noncoding elements such as transcription factor binding sites or small noncoding RNAs. Here, we introduce a new computational method, called Inference of Natural Selection from Interspersed Genomically coHerent elemenTs (INSIGHT), for measuring the influence of natural selection on such elements. INSIGHT uses a generative probabilistic model to contrast patterns of polymorphism and divergence in the elements of interest with those in flanking neutral sites, pooling weak information from many short elements in a manner that accounts for variation among loci in mutation rates and coalescent times. The method is able to disentangle the contributions of weak negative, strong negative, and positive selection based on their distinct effects on patterns of polymorphism and divergence. It obtains information about divergence from multiple outgroup genomes using a general statistical phylogenetic approach. The INSIGHT model is efficiently fitted to genome-wide data using an approximate expectation maximization algorithm. Using simulations, we show that the method can accurately estimate the parameters of interest even in complex demographic scenarios, and that it significantly improves on methods based on summary statistics describing polymorphism and divergence. To demonstrate the usefulness of INSIGHT, we apply it to several classes of human noncoding RNAs and to GATA2-binding sites in the human genome.