Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Inferring recent demography from isolation by distance of long shared sequence blocks

View ORCID ProfileHarald Ringbauer, View ORCID ProfileGraham Coop, Nick Barton
doi: https://doi.org/10.1101/076810
Harald Ringbauer
*Institute of Science and Technology Austria (IST Austria), Am Campus 1, Klosterneuburg A-3400, Austria
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Harald Ringbauer
Graham Coop
†Department of Evolution and Ecology & Center for Population Biology, University of California, Davis, California, United States of America
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Graham Coop
Nick Barton
*Institute of Science and Technology Austria (IST Austria), Am Campus 1, Klosterneuburg A-3400, Austria
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

ABSTRACT

Recently it has become feasible to detect long blocks of almost identical sequence shared between pairs of genomes. These so called IBD-blocks are direct traces of recent coalescence events, and as such contain ample signal for inferring recent demography. Here, we examine sharing of such blocks in two-dimensional populations with local migration. Using a diffusion approximation to trace genetic ancestry back in time, we derive analytical formulas for patterns of isolation by distance of long IBD-blocks, which can also incorporate recent population density changes. As a main result, we introduce an inference scheme that uses a composite likelihood approach to fit observed block sharing to these formulas. We assess our inference method on simulated block sharing data under several standard population genetics models. We first validate the diffusion approximation by showing that the theoretical results closely match simulated block sharing patterns. We then show that our inference scheme rather accurately and robustly recovers estimates of the dispersal rate and effective density, as well as bounds on recent dynamics of population density. To demonstrate an application, we use our estimation scheme to explore the fit of a diffusion model to Eastern European samples in the POPRES data set. We show that ancestry diffusing with a rate of Embedded Image during the last centuries, combined with accelerating population growth, can explain the observed exponential decay of block sharing with pairwise sample distance.

Footnotes

  • ↵1 IST Austria, Am Campus 1, 3400 Klosterneuburg

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted September 23, 2016.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Inferring recent demography from isolation by distance of long shared sequence blocks
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Inferring recent demography from isolation by distance of long shared sequence blocks
Harald Ringbauer, Graham Coop, Nick Barton
bioRxiv 076810; doi: https://doi.org/10.1101/076810
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Inferring recent demography from isolation by distance of long shared sequence blocks
Harald Ringbauer, Graham Coop, Nick Barton
bioRxiv 076810; doi: https://doi.org/10.1101/076810

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genetics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3605)
  • Biochemistry (7575)
  • Bioengineering (5529)
  • Bioinformatics (20806)
  • Biophysics (10333)
  • Cancer Biology (7986)
  • Cell Biology (11644)
  • Clinical Trials (138)
  • Developmental Biology (6610)
  • Ecology (10213)
  • Epidemiology (2065)
  • Evolutionary Biology (13622)
  • Genetics (9543)
  • Genomics (12851)
  • Immunology (7923)
  • Microbiology (19550)
  • Molecular Biology (7666)
  • Neuroscience (42125)
  • Paleontology (308)
  • Pathology (1258)
  • Pharmacology and Toxicology (2203)
  • Physiology (3268)
  • Plant Biology (7044)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1951)
  • Systems Biology (5427)
  • Zoology (1118)