Reconstructing Past Admixture Processes from Local Genomic Ancestry Using Wavelet Transformation

The temporal and genomic scale of selection following hybridization

Genomic evidence supports an important role for selection in shaping patterns of introgression along the genome, but frameworks for understanding the evolutionary dynamics within hybrid populations that underlie these patterns have been lacking. Due to the clock-like effect of recombination in hybrids breaking up parental haplotypes, drift and selection produce predictable patterns of ancestry variation at varying spatial genomic scales through time. Here, we develop methods based on the Discrete Wavelet Transform to study the genomic scale of local ancestry variation and its association with recombination rates and show that these methods capture temporal dynamics of drift and genome-wide selection after hybridization. We apply these methods to published datasets from hybrid populations of swordtail fish (Xiphophorus) and baboons (Papio) and to inferred Neanderthal introgression in modern humans. Across systems, upward of 20% of variation in local ancestry at the broadest genomic scales can be attributed to systematic selection against introgressed alleles, consistent with strong selection acting on early-generation hybrids. Signatures of selection at fine genomic scales suggest selection over longer time scales; however, we suggest that our ability to confidently infer selection at fine scales is likely limited by inherent biases in current methods for estimating local ancestry from contiguous segments of genomic similarity. Wavelet approaches will become widely applicable as genomic data from systems with introgression become increasingly available and can help shed light on generalities of the genomic consequences of interspecific hybridization.

The temporal and genomic scale of selection following hybridization

Genomic evidence supports an important role for selection in shaping patterns of introgression along the genome, but frameworks for understanding the dynamics underlying these patterns within hybrid populations have been lacking. Here, we develop methods based on the Wavelet Transform to understand the spatial genomic scale of local ancestry variation and its association with recombination rates. We present theory and use simulations to show how wavelet-based decompositions of ancestry variance along the genome and the correlation between ancestry and recombination reflect the joint effects of recombination, genetic drift, and genome-wide selection against introgressed alleles. Due to the clock-like effect of recombination in hybrids breaking up parental haplotypes, drift and selection produce predictable patterns of local ancestry variation at varying spatial genomic scales through time. Using wavelet approaches to identify the genomic scale of variance in ancestry and its correlates, we show that these methods can detect temporally localized effects of drift and selection. We apply these methods to previously published datasets from hybrid populations of swordtail fish (Xiphophorus) and baboons (Papio), and to inferred Neanderthal introgression in modern humans. Across systems, we find that upwards of 20% of the variation in local ancestry at the broadest genomic scales can be attributed to systematic selection against introgressed alleles, consistent with strong selection acting on early-generation hybrids. We also see signals of selection at fine genomic scales and much longer time scales. However, we show that our ability to confidently infer selection at fine scales is likely limited by inherent biases in current methods for estimating local ancestry from genomic similarity. Wavelet approaches will become widely applicable as genomic data from systems with introgression become increasingly available, and can help shed light on generalities of the genomic consequences of interspecific hybridization.

Admixture of evolutionary rates across a butterfly hybrid zone

Hybridization is a major evolutionary force that can erode genetic differentiation between species, whereas reproductive isolation maintains such differentiation. In studying a hybrid zone between the swallowtail butterflies Papilio syfanius and Papilio maackii (Lepidoptera: Papilionidae), we made the unexpected discovery that genomic substitution rates are unequal between the parental species. This phenomenon creates a novel process in hybridization, where genomic regions most affected by gene flow evolve at similar rates between species, while genomic regions with strong reproductive isolation evolve at species-specific rates. Thus, hybridization mixes evolutionary rates in a way similar to its effect on genetic ancestry. Using coalescent theory, we show that the rate-mixing process provides distinct information about levels of gene flow across different parts of genomes, and the degree of rate-mixing can be predicted quantitatively from relative sequence divergence ([Formula: see text]) between the hybridizing species at equilibrium. Overall, we demonstrate that reproductive isolation maintains not only genomic differentiation, but also the rate at which differentiation accumulates. Thus, asymmetric rates of evolution provide an additional signature of loci involved in reproductive isolation.

Adaptive introgression from indicine cattle into white cattle breeds from Central Italy

Cattle domestication occurred at least twice independently and gave rise to the modern taurine and indicine cattle breeds. European cattle diversity is generally dominated by taurine cattle, although elevated levels of indicine ancestry have been recorded in several breeds from southern Europe. Here we use genome-wide high-density SNP genotyping data to investigate the taurine and indicine ancestry in southern European cattle, based on a dataset comprising 508 individuals from 23 cattle breeds of taurine, indicine and mixed ancestry, including three breeds from Central Italy known to exhibit the highest levels of indicine introgression among southern European breeds. Based on local genomic ancestry analyses, we reconstruct taurine and indicine ancestry genome-wide and along chromosomes. We scrutinise local genomic introgression signals and identify genomic regions that have introgressed from indicine into taurine cattle under positive selection, harbouring genes with functions related to body size and feed efficiency. These findings suggest that indicine-derived traits helped enhance Central Italian cattle through adaptive introgression. The identified genes could provide genomic targets for selection for improved cattle performance. Our findings elucidate the key role of adaptive introgression in shaping the phenotypic features of modern cattle, aided by cultural and livestock exchange among historic human societies.

Population Structure and Implications on the Genetic Architecture of HIV-1 Phenotypes Within Southern Africa

The interesting history of Southern Africa has put the region in the spotlight for population medical genetics. Major events including the Bantu expansion and European colonialism have imprinted unique genetic signatures within autochthonous populations of Southern Africa, this resulting in differential allele frequencies across the region. This genetic structure has potential implications on susceptibility and resistance to infectious diseases such as human immunodeficiency virus (HIV) infection. Southern Africa is the region affected worst by HIV. Here, we discuss advances made in genome-wide association studies (GWAS) of HIV-1 in the past 12 years and dissect population diversity within Southern Africa. Our findings accentuate that a plethora of factors such as migration, language and culture, admixture, and natural selection have profiled the genetics of the people of Southern Africa. Genetic structure has been observed among the Khoe-San, among Bantu speakers, and between the Khoe-San, Coloureds, and Bantu speakers. Moreover, Southern African populations have complex admixture scenarios. Few GWAS of HIV-1 have been conducted in Southern Africa, with only one of these identifying two novel variants (HCG22rs2535307 and CCNG1kgp22385164) significantly associated with HIV-1 acquisition and progression. High genetic diversity, multi-wave genetic mixture and low linkage disequilibrium of Southern African populations constitute a challenge in identifying genetic variants with modest risk or protective effect against HIV-1. We therefore posit that it is compelling to assess genome-wide contribution of ancestry to HIV-1 infection. We further suggest robust methods that can pin-point population-specific variants that may contribute to the control of HIV-1 in Southern Africa.

Sex-linked genetic diversity originates from persistent sociocultural processes at microgeographic scales

Population genetics has been successful at identifying the relationships between human groups and their interconnected histories. However, the link between genetic demography inferred at large scales and the individual human behaviours that ultimately generate that demography is not always clear. While anthropological and historical context are routinely presented as adjuncts in population genetic studies to help describe the past, determining how underlying patterns of human sociocultural behaviour impact genetics still remains challenging. Here, we analyse patterns of genetic variation in village-scale samples from two islands in eastern Indonesia, patrilocal Sumba and a matrilocal region of Timor. Adopting a 'process modelling' approach, we iteratively explore combinations of structurally different models as a thinking tool. We find interconnected socio-genetic interactions involving sex-biased migration, lineage-focused founder effects, and on Sumba, heritable social dominance. Strikingly, founder ideology, a cultural model derived from anthropological and archaeological studies at larger regional scales, has both its origins and impact at the scale of villages. Process modelling lets us explore these complex interactions, first by circumventing the complexity of formal inference when studying large datasets with many interacting parts, and then by explicitly testing complex anthropological hypotheses about sociocultural behaviour from a more familiar population genetic standpoint.

Human ancestry indentification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

BACKGROUND

While continental level ancestry is relatively simple using genomic information, distinguishing between individuals from closely associated sub-populations (e.g., from the same continent) is still a difficult challenge.

METHODS

We study the problem of predicting human biogeographical ancestry from genomic data under resource constraints. In particular, we focus on the case where the analysis is constrained to using single nucleotide polymorphisms (SNPs) from just one chromosome. We propose methods to construct such ancestry informative SNP panels using correlation-based and outlier-based methods.

RESULTS

We accessed the performance of the proposed SNP panels derived from just one chromosome, using data from the 1000 Genome Project, Phase 3. For continental-level ancestry classification, we achieved an overall classification rate of 96.75% using 206 single nucleotide polymorphisms (SNPs). For sub-population level ancestry prediction, we achieved an average pairwise binary classification rates as follows: subpopulations in Europe: 76.6% (58 SNPs); Africa: 87.02% (87 SNPs); East Asia: 73.30% (68 SNPs); South Asia: 81.14% (75 SNPs); America: 85.85% (68 SNPs).

CONCLUSION

Our results demonstrate that one single chromosome (in particular, Chromosome 1), if carefully analyzed, could hold enough information for accurate prediction of human biogeographical ancestry. This has significant implications in terms of the computational resources required for analysis of ancestry, and in the applications of such analyses, such as in studies of genetic diseases, forensics, and soft biometrics.

Dating admixture events is unsolved problem in multi-way admixed populations

Advances in human sequencing technologies, coupled with statistical and computational tools, have fostered the development of methods for dating admixture events. These methods have merits and drawbacks in estimating admixture events in multi-way admixed populations. Here, we first provide a comprehensive review and comparison of current methods pertinent to dating admixture events. Second, we assess various admixture dating tools. We do so by performing various simulations. Third, we apply the top two assessed methods to real data of a uniquely admixed population from South Africa. Results reveal that current dating admixture models are not sufficiently equipped to estimate ancient admixtures events and to identify multi-faceted admixture events in complex multi-way admixed populations. We conclude with a discussion of research areas where further work on dating admixture-based methods is needed.

Estimating the Timing of Multiple Admixture Pulses During Local Ancestry Inference

Admixture, the mixing of genetically distinct populations, is increasingly recognized as a fundamental biological process. One major goal of admixture analyses is to estimate the timing of admixture events. Whereas most methods today can only detect the most recent admixture event, here, we present coalescent theory and associated software that can be used to estimate the timing of multiple admixture events in an admixed population. We extensively validate this approach and evaluate the conditions under which it can successfully distinguish one- from two-pulse admixture models. We apply our approach to real and simulated data of Drosophila melanogaster We find evidence of a single very recent pulse of cosmopolitan ancestry contributing to African populations, as well as evidence for more ancient admixture among genetically differentiated populations in sub-Saharan Africa. These results suggest our method can quantify complex admixture histories involving genetic material introduced by multiple discrete admixture pulses. The new method facilitates the exploration of admixture and its contribution to adaptation, ecological divergence, and speciation.

Complex Patterns of Admixture across the Indonesian Archipelago

Indonesia, an island nation as large as continental Europe, hosts a sizeable proportion of global human diversity, yet remains surprisingly undercharacterized genetically. Here, we substantially expand on existing studies by reporting genome-scale data for nearly 500 individuals from 25 populations in Island Southeast Asia, New Guinea, and Oceania, notably including previously unsampled islands across the Indonesian archipelago. We use high-resolution analyses of haplotype diversity to reveal fine detail of regional admixture patterns, with a particular focus on the Holocene. We find that recent population history within Indonesia is complex, and that populations from the Philippines made important genetic contributions in the early phases of the Austronesian expansion. Different, but interrelated processes, acted in the east and west. The Austronesian migration took several centuries to spread across the eastern part of the archipelago, where genetic admixture postdates the archeological signal. As with the Neolithic expansion further east in Oceania and in Europe, genetic mixing with local inhabitants in eastern Indonesia lagged behind the arrival of farming populations. In contrast, western Indonesia has a more complicated admixture history shaped by interactions with mainland Asian and Austronesian newcomers, which for some populations occurred more than once. Another layer of complexity in the west was introduced by genetic contact with South Asia and strong demographic events in isolated local groups.

Reconstructing Demography and Social Behavior During the Neolithic Expansion from Genomic Diversity Across Island Southeast Asia

Archaeology, linguistics, and increasingly genetics are clarifying how populations moved from mainland Asia, through Island Southeast Asia, and out into the Pacific during the farming revolution. Yet key features of this process remain poorly understood, particularly how social behaviors intersected with demographic drivers to create the patterns of genomic diversity observed across Island Southeast Asia today. Such questions are ripe for computer modeling. Here, we construct an agent-based model to simulate human mobility across Island Southeast Asia from the Neolithic period to the present, with a special focus on interactions between individuals with Asian, Papuan, and mixed Asian-Papuan ancestry. Incorporating key features of the region, including its complex geography (islands and sea), demographic drivers (fecundity and migration), and social behaviors (marriage preferences), the model simultaneously tracks a full suite of genomic markers (autosomes, X chromosome, mitochondrial DNA, and Y chromosome). Using Bayesian inference, model parameters were determined that produce simulations that closely resemble the admixture profiles of 2299 individuals from 84 populations across Island Southeast Asia. The results highlight that greater propensity to migrate and elevated birth rates are related drivers behind the expansion of individuals with Asian ancestry relative to individuals with Papuan ancestry, that offspring preferentially resulted from marriages between Asian women and Papuan men, and that in contrast to current thinking, individuals with Asian ancestry were likely distributed across large parts of western Island Southeast Asia before the Neolithic expansion.

Recent advances in the study of fine-scale population structure in humans

Empowered by modern genotyping and large samples, population structure can be accurately described and quantified even when it only explains a fraction of a percent of total genetic variance. This is especially relevant and interesting for humans, where fine-scale population structure can both confound disease-mapping studies and reveal the history of migration and divergence that shaped our species' diversity. Here we review notable recent advances in the detection, use, and understanding of population structure. Our work addresses multiple areas where substantial progress is being made: improved statistics and models for better capturing differentiation, admixture, and the spatial distribution of variation; computational speed-ups that allow methods to scale to modern data; and advances in haplotypic modeling that have wide ranging consequences for the analysis of population structure. We conclude by outlining four important open challenges: the limitations of discrete population models, uncertainty in individual origins, the incorporation of both fine-scale structure and ancient DNA in parametric models, and the development of efficient computational tools, particularly for haplotype-based methods.

Small Traditional Human Communities Sustain Genomic Diversity over Microgeographic Scales despite Linguistic Isolation

At least since the Neolithic, humans have largely lived in networks of small, traditional communities. Often socially isolated, these groups evolved distinct languages and cultures over microgeographic scales of just tens of kilometers. Population genetic theory tells us that genetic drift should act quickly in such isolated groups, thus raising the question: do networks of small human communities maintain levels of genetic diversity over microgeographic scales? This question can no longer be asked in most parts of the world, which have been heavily impacted by historical events that make traditional society structures the exception. However, such studies remain possible in parts of Island Southeast Asia and Oceania, where traditional ways of life are still practiced. We captured genome-wide genetic data, together with linguistic records, for a case–study system—eight villages distributed across Sumba, a small, remote island in eastern Indonesia. More than 4,000 years after these communities were established during the Neolithic period, most speak different languages and can be distinguished genetically. Yet their nuclear diversity is not reduced, instead being comparable to other, even much larger, regional groups. Modeling reveals a separation of time scales: while languages and culture can evolve quickly, creating social barriers, sporadic migration averaged over many generations is sufficient to keep villages linked genetically. This loosely-connected network structure, once the global norm and still extant on Sumba today, provides a living proxy to explore fine-scale genome dynamics in the sort of small traditional communities within which the most recent episodes of human evolution occurred.