Evidence map›Paper›PMID 28382466›Full record

ArticleJournal of applied genetics2017

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

Mateus Castelani Freua, Miguel Henrique de Almeida Santana, Ricardo Vieira Ventura, Luis Orlindo Tedeschi, José Bento Sterman Ferraz

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Article in Journal of applied genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mateus Castelani FreuaDepartment of Veterinary Medicine, GMAB, Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.
Miguel Henrique de Almeida SantanaDepartment of Veterinary Medicine, GMAB, Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil. miguel-has@hotmail.com.
Ricardo Vieira VenturaDepartment of Veterinary Medicine, GMAB, Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.
Luis Orlindo TedeschiDepartment of Animal Science, Texas A&M University, 230 Kleberg Center, 2471 TAMU, College Station, TX, 77843, USA.
José Bento Sterman FerrazDepartment of Veterinary Medicine, GMAB, Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Av. Duque de Caxias Norte, 225, Pirassununga, SP, 13635-900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k

Indexed as

Models, GeneticQuantitative Trait LociAnimalsBayes TheoremBody SizeBody WeightCattleGenetic Association StudiesGenotypePhenotypePolymorphism, Single NucleotideBeef cattleGWASMechanistic modelingNellorePerformance

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Registered trials

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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.