Evidence map›Paper›PMID 42538568›Full record

ArticleJournal of animal science and biotechnology2026

Transcriptomic and regulatory landscape of liver tissue associated with meat and carcass quality traits in cattle.

Thais Ribeiro da Silva, Juliana Afonso, Bárbara Silva-Vignato, Ingrid Soares Garcia, Beatriz Delcarme Lima, Heidge Fukumasu, Saulo Luz Silva, Juliana Petrini, Carolina Purcell Goes, Bruna Petry and 6 more

Abstract read
In one paragraph

Article in Journal of animal science and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

16 authors.

Thais Ribeiro da SilvaDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Juliana AfonsoEmbrapa Pecuária Sudeste, São Carlos, SP, Brazil.
Bárbara Silva-VignatoDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Ingrid Soares GarciaDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Beatriz Delcarme LimaDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Heidge FukumasuCollege of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil.
Saulo Luz SilvaCollege of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, Brazil.
Juliana PetriniDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Carolina Purcell GoesDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Bruna PetryDepartment of Animal Science, Iowa State University, Ames, IA, USA.
Wellison J S DinizDepartment of Animal Science, Auburn University, Auburn, AL, USA.
Aline Silva Mello CesarDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
Gerson Barreto MourãoDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil.
James E KoltesDepartment of Animal Science, Iowa State University, Ames, IA, USA.
Luciana Correia de Almeida RegitanoEmbrapa Pecuária Sudeste, São Carlos, SP, Brazil.
Luiz Lehmann CoutinhoDepartment of Animal Science, College of Agriculture "Luiz de Queiroz", University of São Paulo, Piracicaba, SP, Brazil. llcoutinho@usp.br.

Funding

Brazilian National Council of Science (CNPq) for science productivity 303457/2021-0Brazilian National Council of Science (CNPq) for science productivity 304353/2019-1Brazilian National Council of Science (CNPq) for science productivity 310714/2020-6Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.705146/2022-00Fundação de Amparo à Pesquisa do Estado de São Paulo 2019/04089-2Fundação de Amparo à Pesquisa do Estado de São Paulo 2023/08402-2
6 · The paper itself

Abstract

backgroundThe integration of multiple omics strategies represents a transformative paradigm in farm animal genetics and breeding. By capturing molecular complexity across biological layers, integrative omics offers new opportunities to reveal the regulatory mechanisms underlying economically important traits. Here, we characterize the hepatic transcriptomic landscape of Nelore cattle and its relationship with meat and carcass quality phenotypes. For that, we integrated gene expression data, co-expression networks, expression quantitative trait locus (eQTL) mapping, single-nucleotide polymorphism (SNP)-phenotype associations, chromatin accessibility, and transcription factor motif analyses using hepatic RNA-seq data from 90 animals and assay for transposase‑accessible chromatin using sequencing (ATAC-seq) data from two animals.

resultsWeighted gene co-expression network analysis (WGCNA) identified 10 gene modules associated with our phenotypes of interest, particularly the blue module (r = -0.4), which is linked to meat color and enriched in insulin and mTOR signaling pathways. eQTL mapping revealed 1,198 cis- and 39,227 trans-eQTLs (false discovery rate [FDR] < 0.05), including hotspots on chromosome 25. Notably, rs449155362 was found to regulate 848 genes, within them MLXIPL, a transcription factor involved in glucose and lipid metabolism. Phenotype-eQTL associations revealed 54 SNPs (FDR < 0.05) related to meat and carcass traits, among which rs110069409, within an open chromatin region, modulates PLA2G2D1 expression and was associated with meat color (yellowness 24 h after the slaughter-b*₀), representing a convergence point across regulatory layers.

conclusionThese findings provide novel insights into the multilayered genetic architecture of the liver that controls meat quality traits in beef cattle, supporting the use of integrative omics to guide functional genomic selection.

Indexed as

Carcass qualityCattleChromatin accessibilityEQTL mappingMulti-omics integrationWGCNA

Identifiers

PMID42538568
PMCPMC13428424

What Socratic 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 Socratic graph.