Evidence map›Paper›PMID 39466509›Full record

ArticleTropical animal health and production2024

Genetic spatialization in Montana cattle breed.

Nathalia da Silva Costa, Renato Fontes Guimarães, José Bento Sterman Ferraz, Felipe Pimentel, Daniel Pimentel, Tiago do Prado Paim, Luís Telo da Gama, Rafael Núñez-Domínguez, Vanessa Peripolli, Concepta McManus

Abstract read
PubMed Publisher
In one paragraph

Article in Tropical animal health and production, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Nathalia da Silva CostaHumanities Institute, University of Brasilia, Darcy Ribeiro Campus, Brasilia, DF, Brazil.
Renato Fontes GuimarãesHumanities Institute, University of Brasilia, Darcy Ribeiro Campus, Brasilia, DF, Brazil.ORCID https://orcid.org/0000-0002-9555-043X
José Bento Sterman FerrazCollege of Animal Science and Food Engineering, University of Sao Paulo, Pirassununga, Brazil.ORCID https://orcid.org/0000-0002-3874-3104
Felipe PimentelUniversity Anhembi Morumbi, Paulista Campus, São Paulo, SP, Brazil.ORCID https://orcid.org/0000-0001-7016-5255
Daniel PimentelInstitute of Biology, University of Brasilia, Darcy Ribeiro Campus, Brasilia, DF, Brazil.ORCID https://orcid.org/0000-0002-1105-4720
Tiago do Prado PaimFederal Goiano Institute, Rio Verde Campus, Rio Verde, GO, Brazil.ORCID https://orcid.org/0000-0002-9486-7128
Luís Telo da GamaFaculty of Veterinary Medicine, University of Lisbon, Lisbon, LX, Portugal.ORCID https://orcid.org/0000-0003-3894-3488
Rafael Núñez-DomínguezUniversidad Autónoma Chapingo, Texcoco, MX, Mexico.ORCID https://orcid.org/0000-0002-1447-4632
Vanessa PeripolliFederal Catarinense Institute, Araquari Campus, Araquari, SC, Brazil. vanessa.peripolli@hotmail.com.ORCID http://orcid.org/0000-0002-0463-4727
Concepta McManusInstitute of Biology, University of Brasilia, Darcy Ribeiro Campus, Brasilia, DF, Brazil.ORCID https://orcid.org/0000-0002-1106-8962

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico Conselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
6 · The paper itself

Abstract

Brazil is among the world's top beef producers and exporters, and the Montana breed of livestock has gained popularity due to its exceptional meat quality and ability to adapt to the tropical climate. This differentiates it from other breeds, such as the Zebu and Taurine. A methodology that mapped sixteen farms across five Brazilian states was adopted to investigate the link between SNP genetic data and animal collection location. The data was georeferenced using the Geographic Information System and the ArcGIS 10.3 software, considering a geographic coordinate system and the WGS 84 datum. The Alleles in Space (AIS) software was used to study the relationship between the SNP genetic data and the animal collection location. Various analyses were conducted, including the Mantel correlation, genetic barrier identification, and spatial autocorrelation. The results suggest that there is a correlation between genetic and geographical distances, supporting the idea that geographical distance can affect genetic diversity. This information is vital to understand the genetic structure of populations concerning geographical space and is crucial for optimizing Brazilian agricultural production.

Indexed as

Polymorphism, Single NucleotideAnimalsBrazilBreedingCattleGenetic VariationGeographic Information SystemsSpatial AnalysisComposed breedGenetic landscape shapeGeoreferenceMantelSpatial correlation

Identifiers

PMID39466509

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.