The search for genetic functional variants of feed efficiency in Nelore cattle

Detalhes bibliográficos
Ano de defesa: 2021
Autor(a) principal: Ribeiro, Gabriela
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: eng
Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: https://www.teses.usp.br/teses/disponiveis/74/74131/tde-02082021-125049/
Resumo: Feed efficiency (FE) in animal protein production systems is a feature of great importance, since more efficient animals reflect directly on better productivity and sustainability indexes of the production chains. However, the evaluation of this characteristic is complex, slow and costly, which justifies the search for more effective approaches to identify animals regarding FE. A possible strategy is the identification of molecular markers that allow the selection of animals with better or worse FE. Approaches based on studies of broad genome association (GWAS) have generated a lot of information, however in most cases the markers found are not responsible for the phenotypic (causal) effects, which makes the analysis of the results speculative using genes present in large chromosomal windows. Another problem of these studies is that the analyzes are performed from the DNA of any cell, losing the possibility of understanding the functional and tissue-specific importance of the causal variants in a given phenotype. Thus, this work is organized in chapters, where the first one analyzed data generated from RNA-seq from liver biopsy samples from animals of high and low FE, with the objective of identifying functional variants that regulate genes and biological pathways related to the studied phenotype. It was possible to identify 256 variants (247 SNPs and 9 INDELs (insertions and deletions)) distributed in 190 genes that regulate important pathways of innate immunity, which leads to the conclusion that the immune system is one of the main pathways that regulate animal efficiency, be it directly or indirectly. Among the main findings are 4 homozygous variants for highly efficient animals (HFE) in the CFH and CFH5 genes, which are responsible for the phagocytosis of microbes and damaged cells that induce infection, changes in these variants can lead to changes in biological pathways related to immunities, causing economic losses. In the second chapter, data analysis was performed using RNA-seq from several organs (adrenal, hypothalamus, pituitary, liver, muscle), to identify functional variants that can be central regulators, their biological interactions with the efficiency characteristic and finally to validate the results in an independent population. With this research it was possible to identify 169 variants expressed in common in the five tissues, and these variants are mainly related to MHC class I. A total of 144, 252, 413, 416 and 340 potential functional variants (PFVs) were also identified. in the liver, muscle, hypothalamus, pituitary and adrenal, which were adjacent to 223, 422, 694, 697 and 554 SNP markers presented in BovineHD (Illumina), respectively. To perform the validation and genomic predictions for the validation set, the SNP markers adjacent to the PFV were differentially weighted based on the results obtained with ssGWAS using the training set. Through the obtained data and the applied methodology, it was possible to verify that the precision of the prediction increased from 31.03% to 40%, when adding the data of the differently weighted PFVs in the prediction matrix. Through the genomic data obtained and using the methodology of identification of PFVs and validation by ssGWAS, it was possible to develop a consistent pipeline that can be used to improve the breeding programs.
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spelling The search for genetic functional variants of feed efficiency in Nelore cattleA procura por variantes genéticas funcionais da eficiência alimentar em bovinos NeloreCattleEficiência alimentarFeed efficiencyFunctional variantsGadoGWASGWASImmune systemMulti-tecidosMulti-tissuesRNA-seqRNA-seqSistema imunológicoVariantes funcionaisFeed efficiency (FE) in animal protein production systems is a feature of great importance, since more efficient animals reflect directly on better productivity and sustainability indexes of the production chains. However, the evaluation of this characteristic is complex, slow and costly, which justifies the search for more effective approaches to identify animals regarding FE. A possible strategy is the identification of molecular markers that allow the selection of animals with better or worse FE. Approaches based on studies of broad genome association (GWAS) have generated a lot of information, however in most cases the markers found are not responsible for the phenotypic (causal) effects, which makes the analysis of the results speculative using genes present in large chromosomal windows. Another problem of these studies is that the analyzes are performed from the DNA of any cell, losing the possibility of understanding the functional and tissue-specific importance of the causal variants in a given phenotype. Thus, this work is organized in chapters, where the first one analyzed data generated from RNA-seq from liver biopsy samples from animals of high and low FE, with the objective of identifying functional variants that regulate genes and biological pathways related to the studied phenotype. It was possible to identify 256 variants (247 SNPs and 9 INDELs (insertions and deletions)) distributed in 190 genes that regulate important pathways of innate immunity, which leads to the conclusion that the immune system is one of the main pathways that regulate animal efficiency, be it directly or indirectly. Among the main findings are 4 homozygous variants for highly efficient animals (HFE) in the CFH and CFH5 genes, which are responsible for the phagocytosis of microbes and damaged cells that induce infection, changes in these variants can lead to changes in biological pathways related to immunities, causing economic losses. In the second chapter, data analysis was performed using RNA-seq from several organs (adrenal, hypothalamus, pituitary, liver, muscle), to identify functional variants that can be central regulators, their biological interactions with the efficiency characteristic and finally to validate the results in an independent population. With this research it was possible to identify 169 variants expressed in common in the five tissues, and these variants are mainly related to MHC class I. A total of 144, 252, 413, 416 and 340 potential functional variants (PFVs) were also identified. in the liver, muscle, hypothalamus, pituitary and adrenal, which were adjacent to 223, 422, 694, 697 and 554 SNP markers presented in BovineHD (Illumina), respectively. To perform the validation and genomic predictions for the validation set, the SNP markers adjacent to the PFV were differentially weighted based on the results obtained with ssGWAS using the training set. Through the obtained data and the applied methodology, it was possible to verify that the precision of the prediction increased from 31.03% to 40%, when adding the data of the differently weighted PFVs in the prediction matrix. Through the genomic data obtained and using the methodology of identification of PFVs and validation by ssGWAS, it was possible to develop a consistent pipeline that can be used to improve the breeding programs.A eficiência alimentar (EA) em sistemas de produção de proteína animal é uma característica de grande importância, já que animais mais eficientes refletem diretamente em melhores índices de produtividade e sustentabilidade das cadeias produtivas. No entanto, a avaliação desta característica é complexa, lenta e onerosa, o que justifica a busca de abordagens mais eficazes para identificar animais quanto à EA. Uma possível estratégia é a identificação de marcadores moleculares que permitam a seleção de animais com melhor ou pior EA. Abordagens baseadas em estudos de associação ampla do genoma (GWAS) tem gerado bastante informações, porém na maioria das vezes os marcadores encontrados não são os responsáveis pelos efeitos fenotípicos (causais), o que faz com que a análise dos resultados seja especulativa utilizando-se genes presentes em grandes janelas cromossomais. Outro problema destes estudos é que as análises são realizadas a partir do DNA de qualquer célula, se perdendo a possibilidade de compreender a importância funcional e tecido-específica das variantes causais em determinado fenótipo. Assim este trabalho se organiza em capítulos, onde no primeiro foi analisado dados gerados a partir de RNA-seq de amostras de biópsia de fígado de animais de alta e baixa EA, com o objetivo de identificar variantes funcionais que regulem genes e vias biológicas relacionadas com o fenótipo estudado. Foi possível identificar 256 variantes (247 SNPs e 9 INDELs (inserções e deleções)) distribuído em 190 genes que regulam vias importantes da imunidade inata, o que leva a concluir que o sistema imune é uma das principais vias que regulam a eficiência animal, seja direta ou indiretamente. Dentre os principais achados está 4 variantes homozigóticas para animais de alta eficiência alimentar (AEA) nos genes CFH e CFH5, que são responsáveis pela fagocitose de micróbios e células danificadas que induzem à infecção, alterações nessas variantes podem levar a alterações das vias biológicas relacionadas a imunidades, causando perdas econômicas. No segundo capítulo, realizou-se análises de dados a partir de RNA-seq de diversos orgãos (adrenal, hipotálamo, pituitária, fígado, musculo), para identificação de variantes funcionais que podem ser reguladores centrais, suas interações biológicas com a característica de eficiência alimentar e por fim validar os resultados em uma população independente. Com esta pesquisa foi possível identificar 169 variantes expressos em comum nos cinco tecidos, sendo que essas variantes estão relacionadas principalmente com o MHC classe I. Também foram identificados um total de 144, 252, 413, 416 e 340 potenciais variantes funcionais (PVFs) apresentados no fígado, músculo, hipotálamo, hipófise e adrenal, que foram adjacentes a 223, 422, 694, 697 e 554 marcadores SNP apresentados no BovineHD (Illumina), respectivamente. Para realizar a validação e as previsões genômicas para o conjunto de validação, os marcadores SNP adjacentes ao PFV foram diferencialmente ponderados com base nos resultados obtidos com ssGWAS usando o conjunto de treinamento. Através dos dados obtidos e da metodologia aplicada, foi possível constatar que a precisão da predição aumentou de 31,03% para 40%, quando adicionados os dados das PVFs ponderados diferencialmente na matriz de predição. Através dos dados genômicos obtidos e utilizando a metodologia de identificação de PVFs e validação por ssGWAS, foi possível desenvolver um pipeline consistente que pode ser utilizada para a aprimorar os programas de melhoramento genético.Biblioteca Digitais de Teses e Dissertações da USPCesar, Aline Silva MelloFukumasu, HeidgeRibeiro, Gabriela2021-04-05info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/74/74131/tde-02082021-125049/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2021-09-13T20:19:02Zoai:teses.usp.br:tde-02082021-125049Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212021-09-13T20:19:02Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv The search for genetic functional variants of feed efficiency in Nelore cattle
A procura por variantes genéticas funcionais da eficiência alimentar em bovinos Nelore
title The search for genetic functional variants of feed efficiency in Nelore cattle
spellingShingle The search for genetic functional variants of feed efficiency in Nelore cattle
Ribeiro, Gabriela
Cattle
Eficiência alimentar
Feed efficiency
Functional variants
Gado
GWAS
GWAS
Immune system
Multi-tecidos
Multi-tissues
RNA-seq
RNA-seq
Sistema imunológico
Variantes funcionais
title_short The search for genetic functional variants of feed efficiency in Nelore cattle
title_full The search for genetic functional variants of feed efficiency in Nelore cattle
title_fullStr The search for genetic functional variants of feed efficiency in Nelore cattle
title_full_unstemmed The search for genetic functional variants of feed efficiency in Nelore cattle
title_sort The search for genetic functional variants of feed efficiency in Nelore cattle
author Ribeiro, Gabriela
author_facet Ribeiro, Gabriela
author_role author
dc.contributor.none.fl_str_mv Cesar, Aline Silva Mello
Fukumasu, Heidge
dc.contributor.author.fl_str_mv Ribeiro, Gabriela
dc.subject.por.fl_str_mv Cattle
Eficiência alimentar
Feed efficiency
Functional variants
Gado
GWAS
GWAS
Immune system
Multi-tecidos
Multi-tissues
RNA-seq
RNA-seq
Sistema imunológico
Variantes funcionais
topic Cattle
Eficiência alimentar
Feed efficiency
Functional variants
Gado
GWAS
GWAS
Immune system
Multi-tecidos
Multi-tissues
RNA-seq
RNA-seq
Sistema imunológico
Variantes funcionais
description Feed efficiency (FE) in animal protein production systems is a feature of great importance, since more efficient animals reflect directly on better productivity and sustainability indexes of the production chains. However, the evaluation of this characteristic is complex, slow and costly, which justifies the search for more effective approaches to identify animals regarding FE. A possible strategy is the identification of molecular markers that allow the selection of animals with better or worse FE. Approaches based on studies of broad genome association (GWAS) have generated a lot of information, however in most cases the markers found are not responsible for the phenotypic (causal) effects, which makes the analysis of the results speculative using genes present in large chromosomal windows. Another problem of these studies is that the analyzes are performed from the DNA of any cell, losing the possibility of understanding the functional and tissue-specific importance of the causal variants in a given phenotype. Thus, this work is organized in chapters, where the first one analyzed data generated from RNA-seq from liver biopsy samples from animals of high and low FE, with the objective of identifying functional variants that regulate genes and biological pathways related to the studied phenotype. It was possible to identify 256 variants (247 SNPs and 9 INDELs (insertions and deletions)) distributed in 190 genes that regulate important pathways of innate immunity, which leads to the conclusion that the immune system is one of the main pathways that regulate animal efficiency, be it directly or indirectly. Among the main findings are 4 homozygous variants for highly efficient animals (HFE) in the CFH and CFH5 genes, which are responsible for the phagocytosis of microbes and damaged cells that induce infection, changes in these variants can lead to changes in biological pathways related to immunities, causing economic losses. In the second chapter, data analysis was performed using RNA-seq from several organs (adrenal, hypothalamus, pituitary, liver, muscle), to identify functional variants that can be central regulators, their biological interactions with the efficiency characteristic and finally to validate the results in an independent population. With this research it was possible to identify 169 variants expressed in common in the five tissues, and these variants are mainly related to MHC class I. A total of 144, 252, 413, 416 and 340 potential functional variants (PFVs) were also identified. in the liver, muscle, hypothalamus, pituitary and adrenal, which were adjacent to 223, 422, 694, 697 and 554 SNP markers presented in BovineHD (Illumina), respectively. To perform the validation and genomic predictions for the validation set, the SNP markers adjacent to the PFV were differentially weighted based on the results obtained with ssGWAS using the training set. Through the obtained data and the applied methodology, it was possible to verify that the precision of the prediction increased from 31.03% to 40%, when adding the data of the differently weighted PFVs in the prediction matrix. Through the genomic data obtained and using the methodology of identification of PFVs and validation by ssGWAS, it was possible to develop a consistent pipeline that can be used to improve the breeding programs.
publishDate 2021
dc.date.none.fl_str_mv 2021-04-05
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.teses.usp.br/teses/disponiveis/74/74131/tde-02082021-125049/
url https://www.teses.usp.br/teses/disponiveis/74/74131/tde-02082021-125049/
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv
dc.rights.driver.fl_str_mv Liberar o conteúdo para acesso público.
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Liberar o conteúdo para acesso público.
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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dc.publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
publisher.none.fl_str_mv Biblioteca Digitais de Teses e Dissertações da USP
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reponame:Biblioteca Digital de Teses e Dissertações da USP
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Biblioteca Digital de Teses e Dissertações da USP
collection Biblioteca Digital de Teses e Dissertações da USP
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)
repository.mail.fl_str_mv virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br
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