Evidence map›Paper›PMID 38955465›Full record

ReviewGenome research2024

Large-scale genomic analysis of the domestic dog informs biological discovery.

Reuben M Buckley, Elaine A Ostrander

Abstract readReview
In one paragraph

Review in Genome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Integrative MRI and Genomics Analyses PrioritizeAnimals : an open access journal from MDPI · 2026
    Article
  3. Article
  4. Article
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

2 authors.

Reuben M BuckleyNational Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892, USA.ORCID 0000-0001-6334-3906
Elaine A OstranderNational Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892, USA eostrand@mail.nih.gov.

Funding

Comparative Mammalian GenomicsZIAHG200377 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI OSTRANDER, ELAINE · 2012 to 2025
$24.8M
Intramural NIH HHS ZIA HG200377
6 · The paper itself

Abstract

Recent advances in genomics, coupled with a unique population structure and remarkable levels of variation, have propelled the domestic dog to new levels as a system for understanding fundamental principles in mammalian biology. Central to this advance are more than 350 recognized breeds, each a closed population that has undergone selection for unique features. Genetic variation in the domestic dog is particularly well characterized compared with other domestic mammals, with almost 3000 high-coverage genomes publicly available. Importantly, as the number of sequenced genomes increases, new avenues for analysis are becoming available. Herein, we discuss recent discoveries in canine genomics regarding behavior, morphology, and disease susceptibility. We explore the limitations of current data sets for variant interpretation, tradeoffs between sequencing strategies, and the burgeoning role of long-read genomes for capturing structural variants. In addition, we consider how large-scale collections of whole-genome sequence data drive rare variant discovery and assess the geographic distribution of canine diversity, which identifies Asia as a major source of missing variation. Finally, we review recent comparative genomic analyses that will facilitate annotation of the noncoding genome in dogs.

Indexed as

GenomeGenomicsAnimalsDogsGenetic VariationWhole Genome Sequencing

Identifiers

PMID38955465
PMCPMC11293549

What OpenQuestion holds

Textmetadata
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.