Parallel ancient genomic transects reveal complex population history of early European farmers

Lipson, M.; Szecsenyi-Nagy, A.; Mallick, S.; Posa, A.; Stegmar, B.; Keerl, V.; Rohland, N.; Stewardson, K.; Ferry, M.; Michel, M.; Oppenheimer, J.; Broomandkhoshbacht, N.; Harney, E.; Nordenfelt, S.; Llamas, B.; Mende, B. G.; Kohler, K.; Oross, K.; Bondar, M.; Marton, T.; Osztas, A.; Jakucs, J.; Paluch, T.; Horvath, F.; Csengeri, P.; Koos, J.; Sebok, K.; Anders, A.; Raczky, P.; Regenye, J.; Barna, J. P.; Fabian, S.; Serlegi, G.; Toldi, Z.; Nagy, E. G.; Dani, J.; Molnar, E.; Palfi, G.; Mark, L.; Melegh, B.; Banfai, Z.; Fernandez-Eraso, J.; Mujika-Alustiza, J. A.; Alonso Fernandez, C.; Jimenez E

doi:10.1101/114488

Home/Archive/bioRxiv

bioRxiv · 10.1101/114488

Parallel ancient genomic transects reveal complex population history of early European farmers

View original source ↗Export metadata ↓

Abstract

Ancient DNA studies have established that European Neolithic populations were descended from Anatolian migrants who received a limited amount of admixture from resident hunter-gatherers. Many open questions remain, however, about the spatial and temporal dynamics of population interactions and admixture during the Neolithic period. Using the highest-resolution genome-wide ancient DNA data set assembled to date--a total of 177 samples, 127 newly reported here, from the Neolithic and Chalcolithic of Hungary (6000-2900 BCE, n = 98), Germany (5500-3000 BCE, n = 42), and Spain (5500-2200 BCE, n = 37)--we investigate the population dynamics of Neolithization across Europe. We find that genetic diversity was shaped predominantly by local processes, with varied sources and proportions of hunter-gatherer ances try among the three regions and through time. Admixture between groups with different ancestry profiles was pervasive and resulted in observable population transformation across almost all cultural transitions. Our results shed new light on the ways that gene flow reshaped European populations throughout the Neolithic period and demonstrate the potential of time-series-based sampling and modeling approaches to elucidate multiple dimensions of historical population interactions.

Source connections

Published article ↗

Explore related subjects

genetics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Lipson, M., Szecsenyi-Nagy, A., Mallick, S., Posa, A., Stegmar, B., Keerl, V., Rohland, N., Stewardson, K., Ferry, M., Michel, M., Oppenheimer, J., Broomandkhoshbacht, N., Harney, E., Nordenfelt, S., Llamas, B., Mende, B. G., Kohler, K., Oross, K., Bondar, M., Marton, T., Osztas, A., Jakucs, J., Paluch, T., Horvath, F., Csengeri, P., Koos, J., Sebok, K., Anders, A., Raczky, P., Regenye, J., Barna, J. P., Fabian, S., Serlegi, G., Toldi, Z., Nagy, E. G., Dani, J., Molnar, E., Palfi, G., Mark, L., Melegh, B., Banfai, Z., Fernandez-Eraso, J., Mujika-Alustiza, J. A., Alonso Fernandez, C., Jimenez E. 2017-03-06. Parallel ancient genomic transects reveal complex population history of early European farmers. https://doi.org/10.1101/114488

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Cellular context shapes the transcriptomic impact of somatic variants

Somatic SNVs are commonly prioritized by recurrence or sequence annotation, leaving the molecular consequences of private variants unresolved. We developed PrismSNV and Ligo-Seq, a single-cell full-length transcriptome sequencing platform, to quantify transcriptomic displacement associated with within-cell SNV-state toggling. Across 26 samples from three cancer types, more than 60% of candidate SNVs showed significant cell-type-specific displacement with over 30% variation in magnitude. Sequence-based deleteriousness was poorly aligned with cellular displacement, and fewer than 3% of top-displacement SNVs across six tumor types were catalogued in ClinVar. Displacement was strongest in transcriptionally plastic, less differentiated states. Analysis of 655,349 CD4+ T-cell transcriptomes further showed that SNV-gene associations changed in magnitude and sometimes direction during activation. Lack of recurrence or clinical annotation does not imply transcriptomic inertness; variant impact is shaped by cellular context rather than sequence alone, establishing the variant-cell pair as a critical unit for interpreting somatic variation.

genetics↗

bioRxiv2026

Genetic and Epigenetic Landscape of Self-Identified Hispanics/Latino in All Of Us

Human genetic studies still underrepresent many populations, limiting discovery and interpretation of medically relevant variation. Extensive admixture in self-identified Hispanic/Latino populations increases the need for representative reference data and ancestry-aware interpretation of medically relevant variation. We used long-read sequencing to analyze genetic variation, ancestry, and DNA methylation in 1,490 self-identified Hispanic/Latino participants from the All of Us Research Program. We identified 10 million novel variants and more than 100 candidate phenotype associations, with fine-mapping prioritizing structural variants over nearby single-nucleotide variants in more than half. We linked 3,329 tandem repeats to DNA methylation, resolved widespread allele-specific methylation, and identified ancestry-linked regulation across paralogous genes. These results reveal previously inaccessible genetic and regulatory variation and show the value of long-read sequencing for diverse populations.

genetics↗

bioRxiv2026

The genetic architecture of human DNA methylome variation

Population DNA methylome analyses remain largely confined to reference-defined genomic space despite extensive human genetic diversity. A central challenge is therefore to define comparable methylation phenotypes across diverse genomes and map the genetic architecture of methylome variation. Here, using 460 haplotypes from the Human Pangenome Reference Consortium Release 2, we develop two complementary pangenome-based frameworks: one compares methylation within homologous regions while retaining haplotype-specific structural configuration and CpG content; the other represents CpG island (CGI) variation at homologous loci as sequence-resolved alleles. We identified 47,039 CGI alleles, including 8,040 absent from CHM13; 62% were attributable to structural variants and 31% to small variants. Through local genealogies, we reconstructed CGI gain, loss and turnover, revealing how present-day methylation differences align with CGI evolutionary trajectories. We found that genome-wide, methylation variability was buffered against genetic diversity across more than 90% of the genome, with exceptions at extreme nucleotide diversity and locally around structural variants. Our methylation framework enabled population-scale allele-aware methylation quantitative trait locus (mQTL) mapping into non-reference and structurally complex sequence, where mQTL-associated intervals were enriched. mQTLs linked methylation to transcriptomic phenotypes, population differentiation and complex traits, supporting 8% of population differentially methylated regions and colocalizing with more than half of genome-wide association study loci. Together, our study redefines human methylome analysis and our findings reveal a genome-wide architecture of genetic-epigenetic coupling, reshaping how methylation variation is interpreted across human development and disease.

genetics↗