Unraveling the origins of humanity: New research challenges single-origin theory

NewsGuard 100/100 Score

In a recent study published in the journal Nature, researchers explore the differences between various demographic models using diversity-based statistics and linkage disequilibrium.

Study: A weakly structured stem for human origins in Africa. Image Credit: JuliusKielaitis / Shutterstock.com Study: A weakly structured stem for human origins in Africa. Image Credit: JuliusKielaitis / Shutterstock.com

Where did the human species originate?

Previous studies have indicated that the global population likely originated from a single ancestral population in Africa and can be traced through a tree-like model. However, fossil and archaeological records obtained throughout Africa have not confirmed this theory.

Most genetic models assume a tree-like model of isolation with migration; however, other theories, including population calescence and fragmentation or stepping-stone models, have also been proposed. In addition, recent advancements in genomics have allowed novel population-genetic tools to incorporate a ‘ghost’ population to improve genetic data descriptions and how they relate to single-origin models. Nevertheless, these models are also associated with certain limitations, thus reinforcing the need for ancient DNA samples that originated from at least 300 thousand years ago (ka) to fully understand early civilization in Africa.

About the study

In an effort to elucidate the origin of Homo sapiens, the researchers of the current study utilized linkage disequilibrium and diversity-based statistics to discriminate between the different models that have been used to study the evolution of the human species.

The four models considered in the current study included single-population expansion, single-population expansion with regional persistence, archaic hominin admixture, and multi-regional evolution, along with 290 genomes of individuals from southern, eastern, and western Africa and Eurasia. Additionally, samples from British individuals from the 1000 Genomes Project were also included to represent back-to-African gene flow and recent colonial admixture in South Africa. The genomes of Neanderthals from Vindija Cave in Croatia were also included in the analysis to represent gene flow from Neanderthals to areas outside Africa.

Modeling migration and diversity patterns

Models with and without migration between stem populations were considered for studying two types of gene flow during the expansion phase. In the first model, one stem population expands and migrates symmetrically with the other stem populations. Comparatively, in the second model, one or more stem populations expand and receive instantaneous ‘pulse’ events from other stem populations. This subsequently leads to the formation of recent populations following merges from various ancestral populations.

The two models commonly used are continuous migration and multiple-merger models, both of which enable migration between stem branches. However, these models primarily vary in the early divergence of stem populations and their relative effective population size (Ne).

According to the continuous-migration model, stem one diverges into lineages that lead to present-day populations in southern, western, and eastern Africa, while stem 2 provides varying ancestry to those populations. The Mende population exhibits the highest migration from stem two, as compared to the Nama and eastern Africa populations.

Nama individuals were found to exhibit a unique genetic signature that was different from other African populations. This observation indicates that the Nama population has a high level of genetic diversity, which can be supported by their unique geographic location at the southern tip of Africa, which may not have experienced the same level of population drift as other African populations.

Several studies have noted a decrease in coalescence rates from 1 million years ago to 100 ka among humans, which may have increased Ne during the same period. This increase in inferred Ne could be due to either a rise in population size or the ancestral population structure noted in the Middle Pleistocene.

The models, such as the single-origin model, replicate a presumed ancestral rise in Ne from 100 ka to 1 million years ago. The increase in Ne during that period is responsible for the success of the single-origin model, while the best-fit models do not identify any changes in population size but still follow the same pattern.

Relative cross-coalescence rates (RCCRs) are a new method for estimating population divergence by comparing the coalescence rates between two cohorts to the mean within-population coalescence. However, midpoint estimates of RCCR were poor approximates of population divergence, as they underestimated divergence time by almost 50% or more, and recent migration could result in the misordering of divergence events. Thus, RCCR assessments that do not fit several parameters, such as gene flow, should be assessed with caution.

Conclusions

Weakly structured stem models were found to explain patterns of polymorphisms by suggesting that continuous or recurrent contacts occurred between two or more groups that were present in Africa. This observation directly contradicts single population or archaic hominin admixture models; therefore, the genetic diversity that is currently present throughout Africa is likely due to weak gene flow from various ancestral populations over hundreds of thousands of years.

Furthermore, fossil remains that have been obtained from coexisting ancestral populations are likely both genetically and morphologically similar. In fact, the researchers believe that only about 1-4% of genetic differentiation that has been identified among the modern human population is due to genetic drift from stem populations.

Journal reference:
  • Ragsdale, A. P., Weaver, T. D., Atkinson, E. G., et al. (2023). A weakly structured stem for human origins in Africa. Nature; 1-9. doi:10.1038/s41586-023-06055-y
Bhavana Kunkalikar

Written by

Bhavana Kunkalikar

Bhavana Kunkalikar is a medical writer based in Goa, India. Her academic background is in Pharmaceutical sciences and she holds a Bachelor's degree in Pharmacy. Her educational background allowed her to foster an interest in anatomical and physiological sciences. Her college project work based on ‘The manifestations and causes of sickle cell anemia’ formed the stepping stone to a life-long fascination with human pathophysiology.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Kunkalikar, Bhavana. (2023, May 21). Unraveling the origins of humanity: New research challenges single-origin theory. News-Medical. Retrieved on May 25, 2024 from https://www.news-medical.net/news/20230521/Unraveling-the-origins-of-humanity-New-research-challenges-single-origin-theory.aspx.

  • MLA

    Kunkalikar, Bhavana. "Unraveling the origins of humanity: New research challenges single-origin theory". News-Medical. 25 May 2024. <https://www.news-medical.net/news/20230521/Unraveling-the-origins-of-humanity-New-research-challenges-single-origin-theory.aspx>.

  • Chicago

    Kunkalikar, Bhavana. "Unraveling the origins of humanity: New research challenges single-origin theory". News-Medical. https://www.news-medical.net/news/20230521/Unraveling-the-origins-of-humanity-New-research-challenges-single-origin-theory.aspx. (accessed May 25, 2024).

  • Harvard

    Kunkalikar, Bhavana. 2023. Unraveling the origins of humanity: New research challenges single-origin theory. News-Medical, viewed 25 May 2024, https://www.news-medical.net/news/20230521/Unraveling-the-origins-of-humanity-New-research-challenges-single-origin-theory.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Comprehensive study provides new understandings of genomic influences on neuropsychiatric disease