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Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle

BACKGROUND: Potential functional variants (PFVs) can be defined as genetic variants responsible for a given phenotype. Ultimately, these are the best DNA markers for animal breeding and selection, especially for polygenic and complex phenotypes. Herein, we described the identification of PFVs for co...

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Autores principales: Ribeiro, Gabriela, Baldi, Fernando, Cesar, Aline S. M., Alexandre, Pâmela A., Peripolli, Elisa, Ferraz, José B. S., Fukumasu, Heidge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9700932/
https://www.ncbi.nlm.nih.gov/pubmed/36434498
http://dx.doi.org/10.1186/s12864-022-08958-y
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author Ribeiro, Gabriela
Baldi, Fernando
Cesar, Aline S. M.
Alexandre, Pâmela A.
Peripolli, Elisa
Ferraz, José B. S.
Fukumasu, Heidge
author_facet Ribeiro, Gabriela
Baldi, Fernando
Cesar, Aline S. M.
Alexandre, Pâmela A.
Peripolli, Elisa
Ferraz, José B. S.
Fukumasu, Heidge
author_sort Ribeiro, Gabriela
collection PubMed
description BACKGROUND: Potential functional variants (PFVs) can be defined as genetic variants responsible for a given phenotype. Ultimately, these are the best DNA markers for animal breeding and selection, especially for polygenic and complex phenotypes. Herein, we described the identification of PFVs for complex phenotypes (in this case, Feed Efficiency in beef cattle) using a systems-biology driven approach based on RNA-seq data from physiologically relevant organs. RESULTS: The systems-biology coupled with deep molecular phenotyping by RNA-seq of liver, muscle, hypothalamus, pituitary, and adrenal glands of animals with high and low feed efficiency (FE) measured by residual feed intake (RFI) identified 2,000,936 uniquely variants. Among them, 9986 variants were significantly associated with FE and only 78 had a high impact on protein expression and were considered as PFVs. A set of 169 significant uniquely variants were expressed in all five organs, however, only 27 variants had a moderate impact and none of them a had high impact on protein expression. These results provide evidence of tissue-specific effects of high-impact PFVs. The PFVs were enriched (FDR < 0.05) for processing and presentation of MHC Class I and II mediated antigens, which are an important part of the adaptive immune response. The experimental validation of these PFVs was demonstrated by the increased prediction accuracy for RFI using the weighted G matrix (ssGBLUP+wG; Acc = 0.10 and b = 0.48) obtained in the ssGWAS in comparison to the unweighted G matrix (ssGBLUP; Acc = 0.29 and b = 1.10). CONCLUSION: Here we identified PFVs for FE in beef cattle using a strategy based on systems-biology and deep molecular phenotyping. This approach has great potential to be used in genetic prediction programs, especially for polygenic phenotypes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08958-y.
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spelling pubmed-97009322022-11-27 Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle Ribeiro, Gabriela Baldi, Fernando Cesar, Aline S. M. Alexandre, Pâmela A. Peripolli, Elisa Ferraz, José B. S. Fukumasu, Heidge BMC Genomics Research BACKGROUND: Potential functional variants (PFVs) can be defined as genetic variants responsible for a given phenotype. Ultimately, these are the best DNA markers for animal breeding and selection, especially for polygenic and complex phenotypes. Herein, we described the identification of PFVs for complex phenotypes (in this case, Feed Efficiency in beef cattle) using a systems-biology driven approach based on RNA-seq data from physiologically relevant organs. RESULTS: The systems-biology coupled with deep molecular phenotyping by RNA-seq of liver, muscle, hypothalamus, pituitary, and adrenal glands of animals with high and low feed efficiency (FE) measured by residual feed intake (RFI) identified 2,000,936 uniquely variants. Among them, 9986 variants were significantly associated with FE and only 78 had a high impact on protein expression and were considered as PFVs. A set of 169 significant uniquely variants were expressed in all five organs, however, only 27 variants had a moderate impact and none of them a had high impact on protein expression. These results provide evidence of tissue-specific effects of high-impact PFVs. The PFVs were enriched (FDR < 0.05) for processing and presentation of MHC Class I and II mediated antigens, which are an important part of the adaptive immune response. The experimental validation of these PFVs was demonstrated by the increased prediction accuracy for RFI using the weighted G matrix (ssGBLUP+wG; Acc = 0.10 and b = 0.48) obtained in the ssGWAS in comparison to the unweighted G matrix (ssGBLUP; Acc = 0.29 and b = 1.10). CONCLUSION: Here we identified PFVs for FE in beef cattle using a strategy based on systems-biology and deep molecular phenotyping. This approach has great potential to be used in genetic prediction programs, especially for polygenic phenotypes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08958-y. BioMed Central 2022-11-25 /pmc/articles/PMC9700932/ /pubmed/36434498 http://dx.doi.org/10.1186/s12864-022-08958-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ribeiro, Gabriela
Baldi, Fernando
Cesar, Aline S. M.
Alexandre, Pâmela A.
Peripolli, Elisa
Ferraz, José B. S.
Fukumasu, Heidge
Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
title Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
title_full Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
title_fullStr Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
title_full_unstemmed Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
title_short Detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
title_sort detection of potential functional variants based on systems-biology: the case of feed efficiency in beef cattle
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9700932/
https://www.ncbi.nlm.nih.gov/pubmed/36434498
http://dx.doi.org/10.1186/s12864-022-08958-y
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