Neanderthal and Denisovan Population Declines Likely Reflect Geographic Structure, Not Actual Decline

핵심 개념

Geographic population structure and local extinctions can explain the observed declines in Neanderthal effective population size over the last 20,000 years, without requiring an actual decline in the number of individuals.

초록

The article explores mathematical models of geographic population structure to explain the observed patterns in Neanderthal and Denisovan effective population size (Ne) estimates over time.

Key insights:

• The roughly 5-fold decline in Neanderthal Ne over the last 20,000 years is likely an artifact of sampling two genes from the same local deme within a structured population, rather than a real decline in the overall Neanderthal metapopulation.
• Modest rates of local extinction and gene flow between demes can produce substantial reductions in heterozygosity and Ne, even without changes in the total number of individuals.
• Simulations using the island and circular stepping-stone models show that the Neanderthal data are consistent with structured populations, without requiring a real decline in population size.
• The Denisovan data do not show the same decline, but this does not necessarily mean the Denisovan population lacked structure, as such patterns can be variable.
• The results support the hypothesis that the Neanderthal population was geographically structured, as suggested by previous studies using runs of homozygosity.

통계

"If two genes are drawn at random from the population as a whole, their expected coalescence time is 2Nd/(2Nm + 1)."
"The mean coalescence time for a pair of lineages i steps apart is (d - i)i/(M + X)."

인용구

"Not only does Ne change in response to changes in gene flow [17, 20, 33], it may also exhibit a prolonged decline even when there has been no change either in the number of individuals or in the rate or pattern of gene flow [18, 20]."
"If demes never went extinct, the asymptote, Ne(∞), is even larger than Nd, the size of the metapopulation."
"Consequently, the census size of the metapopulation would be larger than Nd."

핵심 통찰 요약

Genetic Evidence for Geographic Structure within the Neanderthal Population

by Rogers,A. R. 게시일 www.biorxiv.org 07-29-2023

https://www.biorxiv.org/content/10.1101/2023.07.28.551046v4

더 깊은 질문

How might the inclusion of additional demographic processes, such as population size changes or fluctuations in migration rates, affect the models and their ability to explain the observed Neanderthal and Denisovan patterns

Including additional demographic processes like population size changes or fluctuations in migration rates could significantly impact the models and their ability to explain the observed Neanderthal and Denisovan patterns.

Population Size Changes: If the models incorporate changes in population size over time, it could lead to fluctuations in effective population size (Ne) that are not solely driven by geographic structure. Sudden expansions or contractions in population size could influence coalescent rates and genetic diversity, potentially altering the patterns observed in the data. For example, a rapid population expansion could result in a temporary increase in Ne, affecting the coalescent rates and the shape of the genetic diversity curves.

Migration Rate Fluctuations: Changes in migration rates between demes could also have a significant impact on the models. Fluctuations in gene flow can affect the rate of genetic exchange between populations, influencing coalescence times and patterns of genetic differentiation. If the models account for varying migration rates over time, they may provide a more nuanced understanding of how gene flow has shaped the genetic diversity of these archaic populations.

By incorporating these additional demographic processes, the models could offer a more comprehensive and realistic representation of the complex dynamics that have influenced the genetic histories of Neanderthals and Denisovans.

What other types of genetic data, beyond effective population size estimates, could be used to further test the hypothesis of geographic structure in these archaic human populations

To further test the hypothesis of geographic structure in Neanderthal and Denisovan populations, researchers could explore additional types of genetic data beyond effective population size estimates. These data could provide complementary insights into the population structure, migration patterns, and demographic history of these archaic human groups. Some potential genetic data sources to consider include:

Genetic Diversity Patterns: Analyzing patterns of genetic diversity across the genomes of Neanderthals and Denisovans could reveal signatures of population structure. Variations in allele frequencies, linkage disequilibrium patterns, and the distribution of genetic variants could provide clues about the extent of gene flow, isolation, and population substructure within these ancient populations.

Admixture Events: Studying admixture events between Neanderthals, Denisovans, and modern humans can shed light on the extent of genetic exchange and interbreeding between different hominin groups. By identifying regions of the genome that show evidence of introgression, researchers can infer past migration events and population interactions.

Ancient DNA Methylation Patterns: Examining DNA methylation patterns in ancient Neanderthal and Denisovan samples could offer insights into epigenetic modifications and gene regulation in these populations. Variations in methylation profiles across individuals or populations could reflect environmental adaptations, population structure, or demographic history.

Functional Genomic Data: Investigating functional genomic data, such as gene expression profiles or protein-coding sequences, can provide information about the biological implications of genetic variation in Neanderthals and Denisovans. Understanding how genetic changes relate to phenotypic traits and adaptations can offer a more holistic view of the population dynamics and evolutionary history of these archaic humans.

By integrating diverse genetic data sources, researchers can enhance their understanding of the genetic relationships, population structure, and demographic trajectories of Neanderthals and Denisovans.

Given the potential for geographic structure to influence effective population size estimates, how might this impact our understanding of the demographic histories of modern human populations

The influence of geographic structure on effective population size estimates can have significant implications for our understanding of the demographic histories of modern human populations.

Interpretation of Population Dynamics: Geographic structure can confound interpretations of population dynamics based on Ne estimates. Fluctuations in Ne driven by spatial subdivision and gene flow may mask or mimic demographic events such as population expansions, contractions, or migrations. Researchers must carefully disentangle the effects of geographic structure from true demographic changes to accurately reconstruct the history of modern human populations.

Impact on Migration Patterns: The presence of geographic structure can affect our interpretation of past migration patterns and gene flow between populations. Estimates of migration rates and connectivity may be influenced by spatial subdivision, leading to potential biases in inferring historical movements of human groups. Understanding the role of geographic structure is crucial for unraveling the complex interplay between migration, isolation, and admixture in shaping modern human genetic diversity.

Population Substructure and Genetic Diversity: Geographic structure can contribute to population substructure and the distribution of genetic diversity within and between human populations. By accounting for spatial effects on genetic variation, researchers can better characterize the genetic relationships, evolutionary processes, and adaptive responses that have shaped the diversity of modern human populations across different regions.

In conclusion, recognizing the impact of geographic structure on effective population size estimates is essential for refining our interpretations of human demographic history and evolutionary dynamics. By considering spatial factors in population genetic analyses, we can gain a more nuanced understanding of the complex interplay between geography, demography, and genetic diversity in modern human populations.