Evidence map›Paper›PMID 39854269›Full record

ArticleGenetics2025

Estimating effective population size trajectories from time-series identity-by-descent segments.

Yilei Huang, Shai Carmi, Harald Ringbauer

Abstract read
In one paragraph

Article in Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Fast simulation of identity-by-descent segments.Bulletin of mathematical biology · 2025
    Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yilei HuangDepartment of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04317, Germany.ORCID 0000-0002-2860-2543
Shai CarmiBraun School of Public Health and Community Medicine, Hebrew University of Jerusalem, Jerusalem 9112102, Israel.ORCID 0000-0002-0188-2610
Harald RingbauerDepartment of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04317, Germany.ORCID 0000-0002-4884-9682

Funding

Max Planck Society
6 · The paper itself

Abstract

Long, identical haplotypes shared between pairs of individuals, known as identity-by-descent (IBD) segments, result from recently shared co-ancestry. Various methods have been developed to utilize IBD sharing for demographic inference in contemporary DNA data. Recent methodological advances have extended the screening for IBD segments to ancient DNA (aDNA) data, making demographic inference based on IBD also possible for aDNA. However, aDNA data typically have varying sampling times, but most demographic inference methods for modern data assume that sampling is contemporaneous. Here, we present Ttne (Time-Transect Ne), which models time-transect sampling to infer recent effective population size trajectories. Using simulations, we show that utilizing IBD sharing in time series increased resolution to infer recent fluctuations in effective population sizes compared with methods that only use contemporaneous samples. To account for IBD detection errors common in empirical analyses, we implemented an approach to estimate and model IBD detection errors. Finally, we applied Ttne to two aDNA time transects: individuals associated with the Copper Age Corded Ware Culture and Medieval England. In both cases, we found evidence of a growing population, a signal consistent with archaeological records.

Indexed as

DNA, AncientGenetics, PopulationModels, GeneticPopulation DensityHaplotypesHumansDNA, Ancientancient DNAbioinformaticsevolutionary biologypopulation geneticsstatistical genetics

Identifiers

PMID39854269
PMCPMC11912830

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.