2021
DOI: 10.3168/jds.2020-18241
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Identification of functional candidate variants and genes for feed efficiency in Holstein and Jersey cattle breeds using RNA-sequencing

Abstract: TRRAP, PIK3CB), which are known to play a key role in the regulation of biological processes that have high metabolic demand and are related to cell growth and regeneration, metabolism, and immune function. The genes identified and their associated functional variants may serve as candidate genetic markers and can be implemented into breeding programs to help improve the selection for feed efficiency in dairy cattle.

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Cited by 22 publications
(15 citation statements)
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“…A recent transcriptome study of the liver in Jersey and Holstein cattle selected for RFI was designed to identify genetic variants from expressed genes in RNA-sequencing data. A polymorphism in KAT2B , a gene involved in the Notch signaling pathway, was identified that segregated with the same RFI phenotypes in both breeds of cattle [ 23 ]. The identification of KAT2B genetic variant associated with RFI, along with the correlation of KAT2B expression with RFI in this study, suggest that KAT2B may be of particular importance for feed efficiency in cattle.…”
Section: Discussionmentioning
confidence: 99%
“…A recent transcriptome study of the liver in Jersey and Holstein cattle selected for RFI was designed to identify genetic variants from expressed genes in RNA-sequencing data. A polymorphism in KAT2B , a gene involved in the Notch signaling pathway, was identified that segregated with the same RFI phenotypes in both breeds of cattle [ 23 ]. The identification of KAT2B genetic variant associated with RFI, along with the correlation of KAT2B expression with RFI in this study, suggest that KAT2B may be of particular importance for feed efficiency in cattle.…”
Section: Discussionmentioning
confidence: 99%
“…Lastly, QTL annotation analysis was performed using the R package: Genomic functional Annotation in Livestock for positional candidate LOci (GALLO) ( https://CRAN.R-project.org/package=GALLO; [ 67 ]). The genome coordinates of the DE transcripts were used, as well as the QTL .gff annotation file retrieved from the cattle QTL Database ( https://www.animalgenome.org/cgi-bin/QTLdb/index [ 49 , 68 ]). We used windows of 1000 bp to account for 100 upstream and 100 downstream of each DE transcript [ 69 ].…”
Section: Methodsmentioning
confidence: 99%
“…The QTL enrichment analysis was performed using GALLO as described by Fonseca et al (2020a). A guilt-by-association approach was performed to identify potential functional candidate genes (Fonseca et al, 2020b;Martins de Carvalho et al, 2020;Sweett et al, 2020;Lam et al, 2021). Briefly, a trained list containing genes associated with stillbirth and pregnancy persistence was obtained from GUILDify (Guney et al, 2014), using the following list of keywords: stillbirth, pregnancy, and pregnancy loss.…”
Section: Functional Candidate Genes Searchmentioning
confidence: 99%