Evidence map›Paper›PMID 41293965›Full record

ArticleMolecular ecology resources2026

Development of High-Throughput Genomic Resources to Inform White-Tailed Deer Population and Disease Management.

David Navarro, Emily K Latch, Anaïs K Tallon, Caitlin N Ott-Conn, Randy W DeYoung, Daniel P Walsh, Peter T Euclide, Chandika R G, Wes A Larson, Arun S Seetharam and 15 more

Abstract read
In one paragraph

Article in Molecular ecology resources, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. A Practical Framework for GT-Seq Panel Optimization.Molecular ecology resources · 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

25 authors.

David NavarroDepartment of Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, USA.ORCID https://orcid.org/0000-0002-7057-3846
Emily K LatchBehavioral and Molecular Ecology Research Group, Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.ORCID https://orcid.org/0000-0002-9892-1056
Anaïs K TallonBehavioral and Molecular Ecology Research Group, Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.
Caitlin N Ott-ConnMichigan Department of Natural Resources, Wildlife Division, Marquette, Michigan, USA.
Randy W DeYoungCaesar Kleberg Wildlife Research Institute, MSC 218, Texas A&M University-Kingsville, Kingsville, Texas, USA.
Daniel P WalshU.S. Geological Survey, Montana Cooperative Wildlife Research Unit, University of Montana, Wildlife Biology Program, Missoula, Montana, USA.
Peter T EuclideDepartment of Forestry and Natural Resources, Illinois-Indiana Sea Grant, Purdue University, West Lafayette, Indiana, USA.ORCID https://orcid.org/0000-0002-1212-0435
Chandika R GBehavioral and Molecular Ecology Research Group, Department of Biological Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA.
Wes A LarsonAlaska Fisheries Science Center, NOAA Alaska Fisheries Science Center, Auke Bay Laboratories, Juneau, Alaska, USA.ORCID https://orcid.org/0000-0003-4473-3401
Arun S SeetharamOffice of Biotechnology, Genome Informatics Facility, Iowa State University, Ames, Iowa, USA.ORCID https://orcid.org/0000-0002-6789-9298
Andrew J SeverinOffice of Biotechnology, Genome Informatics Facility, Iowa State University, Ames, Iowa, USA.
James M ReecyDepartment of Animal Science, Iowa State University, Ames, Iowa, USA.
Zhi-Liang HuDepartment of Animal Science, Iowa State University, Ames, Iowa, USA.
Jay R CantrellSouth Carolina Department of Natural Resources, Columbia, South Carolina, USA.
Michelle CarstensenMinnesota Department of Natural Resources, Wildlife Health Program, 5463 West Broadway, Forest Lake, Minnesota, USA.
Joe N CaudellIndiana Department of Natural Resources, Bloomington, Indiana, USA.
Charlie H KillmasterGeorgia Department of Natural Resources, Wildlife Resources Division, Social Circle, Georgia, USA.
Mitch L LockwoodTexas Parks and Wildlife Department, Kerrville, Texas, USA.
William T McKinleyMississippi Department of Wildlife, Fisheries, and Parks, Jackson, Mississippi, USA.
Andrew S NortonSouth Dakota Game, Fish and Parks, Rapid City, South Dakota, USA.
Krysten L SchulerDepartment of Public and Ecosystem Health Cornell University College of Veterinary Medicine, Ithaca, New York, USA.
Daniel J StormWisconsin Department of Natural Resources, Madison, Wisconsin, USA.
Jason A SumnersMissouri Department of Conservation, Jefferson City, Missouri, USA.
W David WalterU.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit, The Pennsylvania State University, University Park, Pennsylvania, USA.
Julie A BlanchongDepartment of Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, USA.

Funding

Integrated Training For Physician-ScientistsT32GM140935 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI Anna Huttenlocher, Jeniel E Nett · 2021 to 2026
$6.5M
Association of Fish and Wildlife AgenciesIowa State UniversityMichigan Department of Natural ResourcesMichigan State UniversityNIGMS NIH HHS T32 GM140935State of Iowa
6 · The paper itself

Abstract

White-tailed deer (Odocoileus virginianus) are the most abundant and widespread cervid in North America. Genetic data are used as a tool to monitor populations and make management decisions for this game species. However, the development and use of genomic tools that can generate a set of markers suitable for longitudinal genomic data collection, whether for management purposes or to study the demographic and evolutionary processes of widely distributed species, have been challenging. This is mainly due to the cost required to fully implement and interpret the data produced. Here, we generated whole genome resequencing data for 44 free-ranging deer from three regions in their central and eastern North American range and identified over 89 million single nucleotide polymorphisms (SNPs). We used a subset of these SNPs to develop two nested SNP tools, a high-density array (702,183 SNPs) and a medium-density array (72,723 SNPs) to support deer and chronic wasting disease (CWD) management and research. SNPs were selected to ensure an even distribution across scaffolds of the reference genome and include SNPs associated with CWD susceptibility. Using genotyping results for 469 deer from 15 states in the US and Mexico generated by the high-density array and 1335 deer from 18 states generated by the medium-density array, we assessed genotyping success across different populations and explored some insights into population structure. These genomic tools offer a standard set of markers that will enable researchers and managers to address important questions related to white-tailed deer and CWD management. Our SNP arrays also offer the opportunity to examine aspects of white-tailed deer ecology and evolutionary history that were previously difficult to address.

Indexed as

DeerGenotyping TechniquesAnimalsGenetic VariationHigh-Throughput Nucleotide SequencingMalePolymorphism, Single NucleotidePrincipal Component AnalysisUnited StatesWasting Disease, ChronicWhole Genome SequencingDNA microarraygenetic diversityOdocoileus virginianuspopulation structuresingle nucleotide polymorphisms

Identifiers

PMID41293965
PMCPMC12648641

What OpenQuestion holds

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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.