The study of natural variability within human, animal and plant populations has its origins in the work of Darwin; however, understanding the causes of this variability was not possible until the development of Mendelian genetics. Born from the evidence supporting Mendel’s work on heredity, the field of population genetics emerged out of attempts to reconcile Darwinian and Mendelian genetic theories. Population genetics is defined as studying “the genetic composition of biological populations, and the changes in genetic composition that result from the operation of various factors, including natural selection.”
Advances in DNA analysis technology and bioinformatics have extended the classical methods of population genetics, resulting in the emerging science of population genomics. In a broad sense, population genomics examines the variability at multiple loci across the whole genome. Using statistical analysis, it provides a historical perspective on the origins, relationships, migration patterns and other demographics of populations over time.
Population genomics studies originally relied on the methods that form the backbone of forensic DNA analysis—amplification of short tandem repeats (STRs). However, the introduction of microarray technology and massively parallel sequencing (MPS) have facilitated the use of single-nucleotide polymorphisms (SNPs) as genetic markers. SNP analysis provides additional power of discrimination and is more suitable for analyzing degraded DNA samples, compared to STRs.
Population genomics distinguishes between two types of genetic markers: adaptive and neutral. Adaptive loci or genomic regions are those in which variation occurs in response to natural selection—for example, the mutation responsible for lactase persistence in adults, which confers the ability to digest lactose in dairy products. In contrast, neutral loci are those that are not evolving in response to selective pressures. This type of variation usually results from random genetic drift, immigration or population migration. In general, neutral loci across the genome will be similarly affected by demographic changes and the evolutionary history of populations, while loci under selection will often behave differently and reveal outlier patterns of variation (reviewed by Luikert et al., 2003).
The staggering amount of whole-genome data now available from population genomics studies has demanded more powerful and sophisticated methods of statistical analysis. These methods have enabled a deeper understanding of the changing demographics of human populations over time, going back as far as the Neolithic and Mesolithic eras.
Working with Ancient DNA
A time machine would provide an irresistible opportunity to study the behavior and characteristics of human populations over centuries and millennia. Lacking such a device, the next best solution is the analysis of ancient DNA, which is often a multi-disciplinary effort that brings together DNA analysts, historians and archeologists. When working with ancient specimens, the two sampling options available for DNA analysis are usually bones and teeth. Extracting usable DNA from these samples poses unique challenges.
Dr. John Lindo is an Assistant Professor of Anthropology at Emory University in Atlanta, Georgia, and he is intimately familiar with these challenges. Earlier this year, his research group celebrated the opening of a new, state-of-the-art laboratory for ancient DNA analysis, bringing together the molecular and computational aspects of ancient DNA research. “Ancient labs can be costly due to their strict adherence to clean room protocols that aim to prevent contamination,” Dr. Lindo says. The laboratory was designed to create positive air pressure in each room so that air flows out, instead of in, when a door is opened, thereby minimizing the risk of contamination. The laboratory is also designed to inactivate DNA that may be free-floating or on surfaces by constantly dosing rooms with UV radiation. Another limitation of working with ancient DNA, Dr. Lindo notes, is that “amplification of DNA cannot be done in the same building in which the ancient DNA lab is located, due to contamination risk.”
Dr. Lindo’s work with ancient DNA developed from his need to understand evolution and natural selection in human populations by “going back in time”. The availability of technologies such as whole-genome sequencing, which is used extensively in the Lindo laboratory, has proved extremely beneficial. “There are many questions about human evolution,” Dr. Lindo says, “that we can answer with these relatively new methods, that would otherwise have remained intractable.”
Native American Populations
One area of focus for Dr. Lindo’s research group is the regional human population history in the Americas, especially examining how colonization impacted Native American populations. These populations suffered extensive declines associated with the impact of European colonization, and these events would presumably impact genetic variation within the surviving populations. Although previous studies have looked at genetic diversity of contemporary Native American populations, no research has examined ancient Native American genetic diversity.
Dr. Lindo’s team compared whole-exome sequencing data from an ancient indigenous population (before European contact) to their present-day descendants, the Coast Tsimshian people of Prince Rupert Harbor, British Columbia (Lindo et al., 2018). The Tsimshian suffered dramatic population declines, with a 57% reduction in population size, in response to the effects of European contact and smallpox epidemics in the 1800s.
“Genetic variation decreased in populations that experienced a population collapse due to the various negative effects of European contact,” Dr. Lindo says. “These effects included displacement, cultural alterations and devastating disease exposure.” Based on the extent of the population collapse, it would be expected that overall fitness between the ancestral and modern groups would be reduced. Typically, a significant population collapse will result in decreased heterozygosity, due to the reduction in effective population size.
However, Dr. Lindo’s results showed that the changes were more complex. Although the effects of the population collapse associated with European contact appeared to remove a large portion of low-frequency alleles from the population, this reduction was not accompanied by the same expected increase of potentially deleterious genomic features. The most likely reason was the ameliorating effects of allele introgression—the transfer of alleles from one entity to another, genetically divergent entity—caused by admixture. Genetic admixture, which occurs when two previously isolated, genetically distinguishable populations interbreed, results in characteristic DNA signatures that can be analyzed by sophisticated software.
“Native American populations today have proven resilient after the effects of European contact with the increase of genetic diversity since the collapse,” Dr. Lindo says. “Furthermore, there’s evidence that the survivors of the epidemics caused by European-borne disease may have had genetic variants that offered certain Native American populations protection.” Overall, the study provides evidence that the effects of gene flow on indigenous American populations are more subtle than previously thought.
In 1991, the story of “Ötzi the Iceman” captured widespread public attention. The mummified remains of this Copper Age man, dating around 3400–3100 BCE, were discovered in the Ötztal Alps near the Austria-Italy border. Subsequently, whole-genome sequencing in 2012 revealed that Ötzi shared a significant amount of genetic ancestry with the present-day inhabitants of the Mediterranean island of Sardinia (Keller et al., 2012). These results sparked considerable interest in Sardinian population genomics and migration history.
A recent study (Marcus et al., 2020) conducted a detailed analysis of the genetic history of Sardinia and examined how the relationships between Sardinian and mainland populations changed over time. Earlier studies using ancient DNA analysis provided the foundation for the current understanding of how early, geographically distinct European mainland populations showed such a high affinity with modern Sardinians. A popular model suggests that early European farmers accounted for much of the initial Sardinian ancestry, but the island remained relatively isolated from subsequent admixture that occurred on mainland Europe. However, no genome-wide studies had previously been conducted to support this model.
The research team—spanning academic institutions across the US, Germany, Italy, France and Spain—extracted DNA samples from the skeletal remains of 70 Sardinian individuals, dating between 4100 BCE and 1500 CE. The researchers sequenced DNA libraries enriched for the complete mitochondrial genome as well as a targeted set of 1.2 million SNPs, and analyzed the ancient DNA sequencing data together with published autosomal data for both ancient and modern humans in and outside Sardinia. The study covered three periods of Sardinian history: the Sardinian Neolithic (~5700–3400 BCE), the Sardinian Chalcolithic or Copper Age (~3400–2300 BCE) to the Sardinian Bronze Age (~2300–1000 BCE), and the post-Bronze Age period. Several patterns emerged from the study.
The first pattern showed that Sardinian populations in the Middle Neolithic period (4100–3500 BCE) were closely related to the early European farmer populations from mainland Europe. Subsequently, Sardinian genetic ancestry remained stable for an extended period, through the end of the Nuragic period (~900 BCE). The Nuragic period, which began during the Bronze Age around 1800 BCE, is named after the distinctive stone towers, or nuraghe, that can still be seen across Sardinia today. These observations contradict hypotheses that the nuraghe were designed following an influx of people from eastern sources.
Finally, the post-Nuragic period witnessed complex gene flow with both northern and eastern Mediterranean sources. Although the researchers acknowledge that substantial uncertainty exists due to the low differentiation among plausible source populations, their finding of increased variation in ancestry after the Nuragic period supports other ancient DNA studies in the Mediterranean that have observed fine-scale local heterogeneity in the Iron Age and later.
The genetic history of ancient human populations in East Asia is not widely understood, particularly in northern and southern China. Archaeological evidence suggests that East Asian populations were more diverse in the past than they are today, but a lack of sampling makes it difficult to develop a detailed picture of this genetic diversity. A recent study (Yang et al., 2020) provides a fresh look at the genetic history of northern and southern China.
One theory suggests that East Asians have two “layers” of ancestry. The first layer is composed of pre-Neolithic hunter-gatherers, while the second consists of agricultural populations that spread across Asia from the early Neolithic to the present era. To gain more insight into these populations, the researchers obtained ancient DNA samples from individuals who lived across East Asia between 9,500 to 300 years ago. The team enriched the DNA samples for mitochondrial DNA and for nuclear DNA at 1.2 million SNPs before sequencing.
The genome-wide data from Neolithic humans revealed the closest genetic relationship to present-day East Asians who belong to the “second layer”. While more divergent ancestries could be found in Southeast Asia and the Japanese archipelago, Neolithic populations in northern and southern China already displayed genetic features belonging to present-day East Asians. Thus, the results did not support the two-layer model of genetic dispersion in East Asia. A direct comparison of Neolithic East Asians with present-day East Asians and early Asians showed that Neolithic East Asians tend to be more closely related to present-day East Asians than to any early Asian populations.
The researchers also observed that the spread of northern East Asian ancestry led to increased admixture in both directions, such that most of the present-day East Asian population is a mixture of northern and southern East Asian ancestries. Since this extensive admixture was not observed in the Neolithic, much of the human movement that contributed to present-day East Asian genetic patterns must have occurred after the Neolithic period.
Further, the team observed different coastal connections in Neolithic populations from as far north as coastal Siberia and the Japanese archipelago to as far south as coastal Vietnam, implying that that gene flow among coastal populations in East Asia is a common trend. They conclude that genetic sampling from the Paleolithic and from populations further inland in central China should help to further clarify the relationships among Paleolithic hunter-gatherers, Neolithic farmers, and present-day populations of East Asia.
In summary, ancient DNA analysis offers new insights into the ancestry and migration of human populations across the globe. Multidisciplinary efforts that combine DNA analysis, historical records and archeological evidence will continue to provide more information about our past and present—and, hopefully, guide the decisions that shape our future.
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