The Past, Present and Future of Population Genomics

Population genomics refers to the large-scale study of genetic variation both within and between populations of organisms, such as humans.

“Population genomics, in its simplest form, requires genetic information from a group or population with a well-understood structure, to be compared against the same type of genetic information from a different group,” explained Stewart McCulloch, head of laboratory development at UK Biocentre Ltd. “This genetic data can range from a short, targeted read of a specific fragment to a complete genome.”

Population genomics tools: A brief history and evolution

Population genomics evolved from population genetics, a discipline that dates back to the early 1900s.

Population genetics is considered to have been pioneered by the combined contributions of three scientists: Ronald Fisher, John Burdon Sanderson (JBS) Haldane and Sewall Wright, who were able to connect the principles of Mendelian genetics with the Darwinian theory of natural selection, marking a crucial step toward a unified theory of evolution.¹

Early population geneticists were limited to observing genetic variation indirectly through phenotypic variation. But throughout the 20th century, our knowledge of DNA's molecular structure and the role that genes play expanded dramatically.² New technologies for determining the sequence of nucleotide bases in a length of DNA – i.e., gene sequencing – became increasingly efficient and of a lower cost. This enabled scientists to directly examine genetic variation in populations by sampling individuals and looking at a specific gene or loci of interest.

More recently, advancements in computational and molecular biology, such as the introduction of next-generation sequencing (NGS) and high-density microarrays, have enabled the study of genetic variation at an unprecedented scale. Moving beyond the analysis of single genes, entire genomes can now be examined efficiently and at a low cost, leading to the emergence of the rapidly growing field of population genomics.

“Population genomics has continued to evolve over time, but it has undergone three major leaps forward since the earliest genetic assay results were obtained,” said McCulloch.

“First is the advent of high-throughput sequencing, which, alongside the development of NGS technologies, has drastically reduced the cost of conducting such investigations. At the same time, it has increased the volume of information generated, reduced the amount of starting material required and enabled global comparisons on an unprecedented scale,” he added.

The second major leap, according to McCulloch, is the rise of the internet and global computing capabilities: “With their collective capacity to store, analyze, process and interpret increasingly large datasets, these have transformed the field.”

“Not only has this enabled the exploration of new criteria, but it has also decentralized research efforts. Investigators from across the world can now collaborate more easily, bringing diverse skill sets to bear on complex questions – without the previous limitations imposed by data volume,” he added.

The third and final leap is the introduction of artificial intelligence and large language models. “Although still in its infancy and arguably the most controversial advancement, this has already had a significant impact,” McCulloch emphasized.

“These technologies are helping to reduce computational and analytical timeframes, while also beginning to reveal the potential to extract new insights from existing datasets.”

Population genomics: Example applications

Population genomics plays an important role in revealing population structure, genomic variation, natural selection and gene flow in a variety of different organisms.³

For instance, population genomics approaches were utilized to genetically characterize SARS-CoV-2 lineages during the COVID-19 pandemic.⁴

A recent study by Zhao et al. highlighted the power of population genomics in tracing the origins and evolutionary history of key crops, such as wheat.⁵ The researchers analyzed whole-genome sequences of 795 wheat varieties to explore the history of bread wheat. “We found that bread wheat originated from the southwest coast of the Caspian Sea and underwent a slow speciation process, lasting ~3,300 yr owing to persistent gene flow from its relatives,” the authors said. This research could help guide future efforts in protecting wheat biodiversity, as the crop provides a significant portion of the world’s calories and protein.

Population genomics studies can also help identify variants responsible for wildlife’s adaptation to changing environments, enabling conservation efforts to assess a population’s potential to evolve in response to environmental changes, such as global warming.⁶

In human studies, population genomics is advancing our understanding of diseases and leading to improvements in healthcare.

“By combining insights into genetic variation, evolutionary processes and population structure – particularly in human populations – population genomics enables a deeper understanding of both current and future health and disease burdens affecting the group under study,” McCulloch said.

Large-scale population genomics studies can help monitor the genetic diversity of populations worldwide, offering critical information about genetic variation, susceptibility to diseases and the effectiveness of global health initiatives.

Some of the most influential human population genomics studies include:

• The Human Genome Project (HGP), considered the “moonshot” project of modern genetics, produced the first draft sequence of the human genome in 2003.
• The 1000 Genomes Project, which created the largest public database of human variation and genotype data, ran between 2008–2015.  
• The National Genomic Research Library, created to house genomic data from patients and family members in the UK in order to support thousands of research projects.

McCulloch explained how referring to these studies as “completed” can be misleading: “Ongoing research and new analyses continue to be conducted, though the initial collection of source material for these projects is complete.”

“Similarly, the UK Biobank collection has been, and continues to be, utilized in multiple studies. Currently, the largest study still in the process of sample collection in the UK is Our Future Health,” he added.

In the US, The All of Us Research Program – part of the National Institutes of Health – is a longitudinal cohort study that aims to enroll at least one million participants to accelerate biomedical research and enhance human health. It continues to collect genomic data on participants, creating a diverse resource for research purposes.

Challenges and future perspectives in population genomics

In the future, McCulloch envisions a world where every child has their genome sequenced after birth.

“The concept of conducting comprehensive genomic analysis for every newborn child across the global population could enable country- and region-specific interventions – allowing for the immediate treatment of certain conditions and risks, while also providing time to develop tailored treatments and support for individuals as they grow older,” he said.

“Taken to its fullest extent, this approach could even involve annual or regular genomic check-ups to predict an individual’s health needs for the coming year. This would support efforts to maximize quality of life and longevity, while clearly identifying risk factors for disease and illness – potentially preventing pandemics, epidemics and disease burdens before they even begin.”

While this approach is not yet routine clinical practice, research is exploring its potential. The Generation Study, led by Genomics England in partnership with NHS England, is testing newborn babies’ blood samples for over 200 genetic conditions using whole-genome sequencing. The study data will be stored in the National Genomic Research Library, where it will be accessible to authorized researchers for approved research purposes.

As exciting as these prospects are, some challenges remain in population genomics – most notably, the uncertainty of not knowing what you don't yet understand. “The complexity and size of a genome is a challenge in itself, but understanding the interactions between entirely separate sections or regions adds a further layer of complexity,” McCulloch said.

“Data suggesting that a specific health issue is associated with a particular gene or region can be incredibly useful but may later be disproved as new evidence emerges elsewhere. This uncertainty is often addressed by approaching all analyses with an open mindset – much like beginning to assemble a puzzle without knowing the final picture,” he added.

A further challenge lies in collecting enough high-quality samples from a range of demographics to ensure data is both meaningful and representative of the population being studied. “The only effective way to mitigate this is through widespread public engagement and recruitment campaigns, built around a clear research question and well-defined goals,” McCulloch said.

Far from a “silver bullet”

Population genomics has made significant contributions to our understanding of genetic variation, evolutionary processes and human health.  While the field faces challenges, particularly in data complexity and the need for diverse samples, ongoing advancements in technology and collaborative efforts are paving the way for enhanced data analysis and impactful studies.

Nonetheless, McCulloch cautions that it is important to remember that genomics is not a “silver bullet” for understanding disease and health. Rather, it is one tool in our arsenal.

“Population genomics is a valuable tool that can aid in understanding the health of a population, but there will always be exceptions. Until humanity fully comprehends the extent of genetic diversity, interactions and outliers, genomics should only ever be used as an indicator – one that warrants further thorough investigation and examination,” he concluded. 

References: 

1. Okazaki A, Yamazaki S, Inoue I, Ott J. Population genetics: past, present, and future. Hum Genet. 2021;140(2):231-240. doi: 10.1007/s00439-020-02208-5

2. Charlesworth B, Charlesworth D. Population genetics from 1966 to 2016. Heredity. 2017;118(1):2-9. doi: 10.1038/hdy.2016.55

3. Lu Y, Li M, Gao Z, et al. Advances in whole genome sequencing: Methods, tools, and applications in population genomics. Int J Mol Sci. 2025;26(1). doi:10.3390/ijms26010372

4. Mostefai F, Gamache I, N’Guessan A, et al. Population genomics approaches for genetic characterization of SARS-CoV-2 lineages. Front in Med. 2022. doi: 10.3389/fmed.2022.826746

5. Zhao X, Guo Y, Kang L, et al. Population genomics unravels the Holocene history of bread wheat and its relatives. Nat Plants. 2023;9(3):403-419. doi: 10.1038/s41477-023-01367-3

6. Hohenlohe PA, Funk WC, Rajora OP. Population genomics for wildlife conservation and management. Mol Ecol. 2021;30(1):62-82. doi: 10.1111/mec.15720