Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs

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Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs. / Ibragimov, Emil; Pedersen, Anni Øyan; Xiao, Liang; Cirera, Susanna; Fredholm, Merete; Karlskov-Mortensen, Peter.

I: Scientific Reports, Bind 12, 21946, 2022.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Ibragimov, E, Pedersen, AØ, Xiao, L, Cirera, S, Fredholm, M & Karlskov-Mortensen, P 2022, 'Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs', Scientific Reports, bind 12, 21946. https://doi.org/10.1038/s41598-022-26496-1

APA

Ibragimov, E., Pedersen, A. Ø., Xiao, L., Cirera, S., Fredholm, M., & Karlskov-Mortensen, P. (2022). Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs. Scientific Reports, 12, [21946]. https://doi.org/10.1038/s41598-022-26496-1

Vancouver

Ibragimov E, Pedersen AØ, Xiao L, Cirera S, Fredholm M, Karlskov-Mortensen P. Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs. Scientific Reports. 2022;12. 21946. https://doi.org/10.1038/s41598-022-26496-1

Author

Ibragimov, Emil ; Pedersen, Anni Øyan ; Xiao, Liang ; Cirera, Susanna ; Fredholm, Merete ; Karlskov-Mortensen, Peter. / Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs. I: Scientific Reports. 2022 ; Bind 12.

Bibtex

@article{da8b4032b1d34326a44450777c0c4a33,
title = "Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs",
abstract = "Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.",
author = "Emil Ibragimov and Pedersen, {Anni {\O}yan} and Liang Xiao and Susanna Cirera and Merete Fredholm and Peter Karlskov-Mortensen",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",
year = "2022",
doi = "10.1038/s41598-022-26496-1",
language = "English",
volume = "12",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - Analysis of merged transcriptomic and genomic datasets to identify genes and pathways underlying residual feed intake in growing pigs

AU - Ibragimov, Emil

AU - Pedersen, Anni Øyan

AU - Xiao, Liang

AU - Cirera, Susanna

AU - Fredholm, Merete

AU - Karlskov-Mortensen, Peter

N1 - Publisher Copyright: © 2022, The Author(s).

PY - 2022

Y1 - 2022

N2 - Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.

AB - Improvement of feed efficiency (FE) in pigs is an important milestone in order to reduce the economic and environmental impact of pig production. The goal of finding biomarkers for FE has persisted for decades. However, due to the complexity of the FE trait, these goals have still not been met. Here, we search for quantitative trait loci (QTL), candidate genes, and biological pathways associated with FE using both genotype and RNA-seq data. We obtained genotype and colon epithelium RNA-seq data for 375 and 96 pigs, respectively. In total, a genome-wide association study (GWAS) and differential expression (DE) analysis led to detection of three QTL on SSC9 and 17 DE-genes associated with FE. Possible intersection points between genes located in QTL and DE-genes were found on levels of transcription factor-target interaction. Moreover, cis-eQTL analysis revealed associations between genotype and expression levels of three DE-genes and three genes located in the GWAS QTLs, which may establish the connection between genotype and phenotype through DE. Finally, single nucleotide polymorphism calling using RNA-seq data for genes located in GWAS QTLs revealed 53 polymorphisms of which eleven were missense variants.

U2 - 10.1038/s41598-022-26496-1

DO - 10.1038/s41598-022-26496-1

M3 - Journal article

C2 - 36536008

AN - SCOPUS:85144327269

VL - 12

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 21946

ER -

ID: 330900972