Evidence map›Paper›PMID 34552971›Full record

ReviewFrontiers in veterinary science2021

Advancing Genetic Selection and Behavioral Genomics of Working Dogs Through Collaborative Science.

Frances L Chen, Madeline Zimmermann, Jessica P Hekman, Kathryn A Lord, Brittney Logan, Jane Russenberger, Eldin A Leighton, Elinor K Karlsson

Abstract readReview
In one paragraph

Review in Frontiers in veterinary science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Review
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  5. GWAS for behavioral traits in golden retrievers identifies genes implicated in human temperament, mental health, and cognition.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  6. Absence ofVeterinary sciences · 2025
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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

8 authors.

Frances L ChenVertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.
Madeline ZimmermannGuiding Eyes for the Blind, Yorktown Heights, NY, United States.
Jessica P HekmanVertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.
Kathryn A LordVertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.
Brittney LoganVertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.
Jane RussenbergerGuiding Eyes for the Blind, Yorktown Heights, NY, United States.
Eldin A LeightonInternational Working Dog Breeding Association, San Antonio, TX, United States.
Elinor K KarlssonVertebrate Genomics, Broad Institute of MIT and Harvard, Cambridge, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ancient partnership between people and dogs is struggling to meet modern day needs, with demand exceeding our capacity to safely breed high-performing and healthy dogs. New statistical genetic approaches and genomic technology have the potential to revolutionize dog breeding, by transitioning from problematic phenotypic selection to methods that can preserve genetic diversity while increasing the proportion of successful dogs. To fully utilize this technology will require ultra large datasets, with hundreds of thousands of dogs. Today, dog breeders struggle to apply even the tools available now, stymied by the need for sophisticated data storage infrastructure and expertise in statistical genetics. Here, we review recent advances in animal breeding, and how a new approach to dog breeding would address the needs of working dog breeders today while also providing them with a path to realizing the next generation of technology. We provide a step-by-step guide for dog breeders to start implementing estimated breeding value selection in their programs now, and we describe how genotyping and DNA sequencing data, as it becomes more widely available, can be integrated into this approach. Finally, we call for data sharing among dog breeding programs as a path to achieving a future that can benefit all dogs, and their human partners too.

Indexed as

behaviordog breedingEBVgenetic selectiongenomicsguide dogheritabilityworking dog

Identifiers

PMID34552971
PMCPMC8450581

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.