{
  "id": 5667225,
  "title": "SweepLink: Joint Inference of Demography and Linked~Selection from Time-series Data",
  "url": "https://urgent.news/2026/09/04/sweeplink-joint-inference-of-demography-and-linked-selection-from",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-04T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.02.748944v1?rss=1"
  },
  "original_language": "en",
  "account": "Genome-wide time-series data, such as allele frequency trajectories tracked over multiple sampling points, provide rich information for inferring selection. In addition to a beneficial allele's rise in frequency, this data shows how it pulls adjacent loci up through a phenomenon called genetic hitch-hiking. However, most existing tools analyze loci independently, inferring site-specific selection coefficients in isolation and relying on ad hoc window statistics to account for hitch-hiking. Many of these tools also require a defined population size or struggle when jointly inferring selection and demography, and their power is highly dependent on a significance threshold. To tackle these issues, researchers have developed SweepLink, a novel two-layer Hidden Markov Model that jointly infers both demography and linked selection across the entire genome. This approach features a spatial layer that captures correlations between neighboring selection coefficients, combined with a temporal Wright-Fisher diffusion layer. As demonstrated through extensive simulations, SweepLink better distinguishes drift-driven false positives from true loci receiving support from neighboring loci, thereby enhancing sensitivity to weak and moderate selection while maintaining the detection power of existing tools for strong selection. Notably, the simulations show that SweepLink produces confident posterior probabilities that remain stable even at maximal significance, eliminating the need for arbitrary thresholds. The researchers applied SweepLink to ancient DNA time-series data from the British population, previously analyzed using a single-locus tool. SweepLink successfully recovers four of the previously identified signals (LCT, SLC45A2, DHCR7, HERC2), and partially recovers the MHC/HLA signal. Additionally, it uncovers several new candidate regions, including DPYD, FADS1/2, and OAS1, which were missed by the prior scan but supported by independent studies.",
  "summary": "Genome-wide time-series data, i.e. allele frequency trajectories tracked across multiple sampling times, are among the richest sources of information for inferring selection. Beyond a beneficial allele's own rise in frequency, such data capture how it drags nearby loci upward via linkage, an effect known as genetic hitch-hiking. Yet most existing tools are single-locus, treating loci…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}