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Despite the ubiquity of wild boar populations across Eurasia, their origins, routes of dispersal, and phenotypic evolution remain uncertain. Here, using 745 genomes representing populations across Eur...

Transposable elements mobilize within and occasionally between genomes, including from host to virus. We identified two insertions of the human BC200 noncoding RNA gene in the poxvirus molluscum conta...

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Single-nucleus RNA sequencing captures molecular changes in the prefrontal cortex across the lifespan and in health and disease.

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Abstract. Stabilizing selection commonly acts on complex traits that affect individual fitness. Here, we relate mean fitness under stabilizing selection to

The Department of Biology at Stanford University seeks applicants for a tenure-track Assistant Professor in Evolutionary Biology. A successful candidate will conduct research that asks fundamental que...

The Life Sciences Departments in Harvard Faculty of Arts and Sciences seek to recruit a tenure-track professor whose research is at the interface of AI and life sciences, from methodological developments to AI-enabled discovery. The successful candidate will be appointed in one of the participating

The Carlson Lab works at the interface of population and quantitative genetics, statistics, and evolutionary biology.

Biobank-scale genomic analyses are increasingly constrained by computational costs, as hundreds of thousands to millions of samples and variants must be analyzed together. The genotype representation ...

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Nature Reviews Genetics, Published online: 11 September 2026; doi:10.1038/s41576-026-01010-9Advances in genome-wide selection scans and ancient DNA have greatly expanded our ability to study human evolution. This Review discusses the conceptual and statistical challenges in identifying and interpreting selection signals, and how recent approaches are reshaping our understanding of human evolution over the past 10,000 years.

We are recruiting PhD students in Evolutionary Genomics for Fall 2027 at Rice University!  Projects in the lab include investigating the causes and consequences of recombination rate variation, the...

Ancient DNA and new inference methods have transformed the study of human origins, but consensus has not followed. Evidence increasingly indicates that hominin populations were pervasively structured ...

GPN-Star, a genomic language model with a phylogeny-aware architecture for whole-genome alignment data, is shown to be a scalable and flexible tool for genetic variant effect prediction across species...

AbstractMotivation. Recent advances in inference of the ancestral recombination graph (ARG), which describes how segments of chromosomes trace back through

Large-scale genome initiatives are transforming biodiversity genomics, but genomes remain taxonomically sparse and difficult to compare across species. Kapli and colleagues argue that natural history ...

The authors present Gnomix, a local ancestry framework that delivers leading accuracy across diverse admixed datasets on both whole-genome and array data with high efficiency, together with Gnofix, it...

A dynamic atlas of gene regulation was generated by perturbing every expressed gene across 22 million primary human CD4+ T cells under resting conditions and following re-stimulation. The resulting ma...

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Newly developed methods enable construction of Icelandic haplotypes and mapping of population-scale short reads to a pangenome by reducing reference bias and improving discovery in low-mappability reg...

Many questions in population genetics are concerned with reconstructing evolutionary history through time, such as inferring how population structure has changed throughout the past. Yet, many existing approaches have only an implicit temporal component, using quantities such as allele frequency or haplotype length as rough proxies for age. Recent advances in the inference of Ancestral Recombination Graphs (ARGs) have made it possible to estimate the entire sequence of local genealogies along the genome. These genealogies explicitly encode how samples are related to each other at different time points in the past, enabling the inference of how population structure has changed over time. To this end, recent work has used ARGs to define time-stratified versions of widely-used population genetics summary statistics in an attempt to capture the population structure present within a particular time window. Here, we show that naive approaches result in statistics that cannot be interpreted solely in terms of the population structure present within the time window they are targeting. To address this problem, we introduce a framework of coalescent-based time-stratified statistics, which use coalescence probabilities to partition classical summary statistics into interval-specific contributions. Using coalescent simulations, we demonstrate that these statistics accurately isolate population structure at different temporal depths and avoid spurious signals. Our results highlight the necessity of integrating coalescent theory into ARG-based temporal analyses and provide a principled and practical foundation for studying the dynamics of population structure through time. ### Competing Interest Statement The authors have declared no competing interest. National Human Genome Research Institute, https://ror.org/00baak391, R01HG014005