Evidence map›Paper›PMID 38166730›Full record

ArticleBMC genomics2024

Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs.

Felipe André Oliveira Freitas, Luiz F Brito, Simara Larissa Fanalli, Janaína Lustosa Gonçales, Bruna Pereira Martins da Silva, Mariah Castro Durval, Fernanda Nery Ciconello, Camila Sabino de Oliveira, Lucas Echevarria Nascimento, Izally Carvalho Gervásio and 6 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 11% of its field
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

6 citing papers in PubMed, 5 citations in OpenAlex.

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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

16 authors at 3 institutions in 3 countries.

Felipe André Oliveira FreitasLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Luiz F BritoDepartment of Animal Sciences, Purdue University, West Lafayette, IN, 47907, USA.
Simara Larissa FanalliFaculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil.
Janaína Lustosa GonçalesLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Bruna Pereira Martins da SilvaLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Mariah Castro DurvalFaculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil.
Fernanda Nery CiconelloLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Camila Sabino de OliveiraLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Lucas Echevarria NascimentoLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Izally Carvalho GervásioLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Julia Dezen GomesLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Gabriel Costa Monteiro MoreiraUnit of Animal Genomics, GIGA-R and Faculty of Veterinary Medicine, University of Liège (B34), Liège, 4000, Belgium.
Bárbara Silva-VignatoFaculty of Animal Science and Food Engineering, University of São Paulo, Pirassununga, 13635- 900, SP, Brazil.
Luiz Lehmann CoutinhoLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil.
Vivian Vezzoni de AlmeidaCollege of Veterinary Medicine and Animal Science, Federal University of Goiás, Goiânia, 74001-970, GO, Brazil.
Aline Silva Mello CesarLuiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, 13416-000, SP, Brazil. alinecesar@usp.br.
Universidade de São Paulo · BRUniversidade Federal de Goiás · BRUniversity of Liège · BE

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 9884374438299747Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001Fundação de Amparo à Pesquisa do Estado de Goiás 202110267000074Fundação de Amparo à Pesquisa do Estado de São Paulo 2017/25180-2Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/01694-2Fundação de Amparo à Pesquisa do Estado de São Paulo 2021/10394-2Fundação de Amparo à Pesquisa do Estado de São Paulo 2022/08142-8Fundação de Amparo à Pesquisa do Estado de São Paulo 2022/10643-5Fundação de Amparo à Pesquisa do Estado de São Paulo 2022/10780-2Fundação de Amparo à Pesquisa do Estado de São Paulo 2023/02067-7
6 · The paper itself

Abstract

backgroundMapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in the Longissimus lumborum tissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs.

resultsThe number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the "Meat and Carcass" type QTL. The scenarios with the highest number of cis- (n = 304) and trans- (n = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes.

conclusionsAfter LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.

Indexed as

Polymorphism, Single NucleotideQuantitative Trait LociAnimalsBody CompositionGenome-Wide Association StudyMuscle, SkeletalPhenotypeSwineExpression quantitative trait lociLD pruningSus scrofaTranscriptomic

Identifiers

PMID38166730
PMCPMC10759680
OpenAlexW4390493046

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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.