Search

Your search keyword '"Alexandre, Pâmela A."' showing total 47 results
Start Over Author "Alexandre, Pâmela A."
47 results on '"Alexandre, Pâmela A."'

5. Combining genomics and semen microbiome increases the accuracy of predicting bull prolificacy.

Author

Alexandre, Pâmela A., Rodríguez‐Ramilo, Silvia T., Mach, Núria, and Reverter, Antonio

Subjects
*LIVESTOCK productivity, *SUSTAINABLE agriculture, *PHENOTYPIC plasticity, *FERTILITY, *INBREEDING
Abstract

Commercial livestock producers need to prioritize genetic progress for health and efficiency traits to address productivity, welfare, and environmental concerns but face challenges due to limited pedigree information in extensive multi‐sire breeding scenarios. Utilizing pooled DNA for genotyping and integrating seminal microbiome information into genomic models could enhance predictions of male fertility traits, thus addressing complexities in reproductive performance and inbreeding effects. Using the Angus Australia database comprising genotypes and pedigree data for 78,555 animals, we simulated percentage of normal sperm (PNS) and prolificacy of sires, resulting in 713 sires and 27,557 progeny in the final dataset. Publicly available microbiome data from 45 bulls was used to simulate data for the 713 sires. By incorporating both genomic and microbiome information our models were able to explain a larger proportion of phenotypic variation in both PNS (0.94) and prolificacy (0.56) compared to models using a single data source (e.g., 0.36 and 0.41, respectively, using only genomic information). Additionally, models containing both genomic and microbiome data revealed larger phenotypic differences between animals in the top and bottom quartile of predictions, indicating potential for improved productivity and sustainability in livestock farming systems. Inbreeding depression was observed to affect fertility traits, which makes the incorporation of microbiome information on the prediction of fertility traits even more actionable. Crucially, our inferences demonstrate the potential of the semen microbiome to contribute to the improvement of fertility traits in cattle and pave the way for the development of targeted microbiome interventions to improve reproductive performance in livestock. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

13. Wagyu Feeder Check: A genomic-based tool to identify performance differences of Australian Wagyu and Wagyu crossed cattle.

Author

Reverter, Antonio, Yutao Li, Alexandre, Pâmela A., Dominik, Sonja, Teseling, Carel, van den Heuvel, Aaron, Schutt, Karen, McDonagh, Matt, and Porto-Neto, Laercio

Abstract

Context. Wagyu Feeder Check is a genomic-based tool designed to provide genomic estimated breeding values (GEBV) for five feedlot growth and carcase traits. At present, Wagyu Feeder Check is based on a reference population of 8316 genotyped and phenotyped Australian fullblood (FB; N = 2120) Wagyu and Wagyu-crossed (XB; N = 6196) cattle, principally Wagyu × Angus F1 animals. Aims. We provide technical details behind the development of the Wagyu Feeder Check and validate the ability of its GEBV to predict differences in performance of Wagyu cattle in daily weight gain at feedlot, carcase weight, carcase eye muscle area, carcase marbling score and carcase rump fat at the P8 site. Methods. Data supplied from eight commercial supply chains across Australia was used to generate GEBV using mixed-model equations that incorporated a genomic relationship matrix build with 82 504 autosomal markers. The bias, dispersion, and accuracy of the GEBV were evaluated using a four-way cross-validation scheme where, in each turn, the phenotypes from a random 1549 (or 25%) XB cattle were set as missing. Key results. The genomic estimate of the Wagyu content in the FB and XB population averaged 99.12% and 59.55%, respectively, and with most of the non-Wagyu content associated with Angus. The estimates of heritability (± s.e.) were 0.497 ± 0.016, 0.474 ± 0.004, 0.347 ± 0.014, 0.429 ± 0.003 and 0.422 ± 0.003 for daily weight gain at feedlot, carcase weight, eye muscle area, marbling and rump fat, respectively. Averaged across the four XB validation populations, the accuracy of GEBV was 0.624, 0.634, 0.385, 0.620, and 0.526 for the same set of traits. Conclusions. Genomic predictions generated by Wagyu Feeder Check can predict differences in feedlot and carcase performance of Australian Wagyu cattle. Given the large content of Angus in the XB population, further research is required to determine the predictive ability of GEBV in Wagyu × Bos indicus and Wagyu × dairy animals. Implications. Commercial feedlot operators finishing animals with a strong Wagyu breed component will benefit from using Wagyu Feeder Check for decision making. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

17. Transcriptome Profile Reveals Genetic and Metabolic Mechanisms Related to Essential Fatty Acid Content of Intramuscular Longissimus thoracis in Nellore Cattle

Author

Schettini, Gustavo Pimenta, primary, Peripolli, Elisa, additional, Alexandre, Pâmela Almeida, additional, dos Santos, Wellington Bizarria, additional, Pereira, Angélica Simone Cravo, additional, de Albuquerque, Lúcia Galvão, additional, Baldi, Fernando, additional, and Curi, Rogério Abdallah, additional

Published
2022
Full Text
View/download PDF

18. Transcriptomic profile of longissimus thoracis associated with fatty acid content in Nellore beef cattle

Author

Schettini, Gustavo Pimenta, primary, Peripolli, Elisa, additional, Alexandre, Pâmela Almeida, additional, dos Santos, Wellington Bizarria, additional, da Silva Neto, João Barbosa, additional, Pereira, Angélica Simone Cravo, additional, de Albuquerque, Lúcia Galvão, additional, Curi, Rogério Abdallah, additional, and Baldi, Fernando, additional

Published
2022
Full Text
View/download PDF

20. Imatinib Mesylate for the Treatment of Canine Mast Cell Tumors: Assessment of the Response and Adverse Events in Comparison with the Conventional Therapy with Vinblastine and Prednisone

Author

Macedo, Thais Rodrigues, primary, de Queiroz, Genilson Fernandes, additional, Casagrande, Thaís Andrade Costa, additional, Alexandre, Pâmela Almeida, additional, Brandão, Paulo Eduardo, additional, Fukumasu, Heidge, additional, Melo, Samanta Rios, additional, Dagli, Maria Lucia Zaidan, additional, Pinto, Ana Carolina B. C. Fonseca, additional, and Matera, Julia Maria, additional

Published
2022
Full Text
View/download PDF

21. Interaction between rumen microbiome and host feed efficiency phenotype across contrasting breeds and dietary sources.

Author

Keogh, Kate, Kenny, David A., Alexandre, Pâmela Almeida, Waters, Sinead, McGovern, Emily, McGee, Mark, and Reverter, Antonio

Subjects
BEEF industry, ANIMAL development, SUSTAINABILITY, CATTLE breeding, ANIMAL products
Abstract

Provision of feed accounts for a high proportion of the variable cost in beef production systems, and consequently is a major determinant of overall profitability. Thus, improving the conversion of feed to animal product by identifying and breeding cattle with improved feed efficiency potential provides a method through which feed input costs may be reduced, whilst also contributing to more environmentally sustainable beef production. The rumen microbiome dictates the feed degradation capacity and subsequent nutrient supply in ruminants and is thus potentially impacted by feed efficiency phenotype. However, the relationship between rumen microbiota and host feed efficiency phenotype is yet to be fully elucidated. This is further complicated when contrasting diets, cattle breeds as well as various stages of animal development are considered. The objective of this study was to undertake network analysis on rumen microbiome data generated from two contrasting steer breed types (Charolais and Holstein-Friesian), divergent within-breed for residual feed intake (RFI), and offered contrasting diets during different stages of development: i) high-concentrate during the growing phase; ii) grass silage during the growing phase; iii) zero-grazed grass during the growing phase, and iv) high-concentrate during the finishing phase. From approximately 10 mo of age, Charolais (n = 90) and Holstein-Friesian (n = 77) steers were individually fed each of the aforementioned diets for 70 d, following an adaptation period between each diet. At the end of each dietary phase, RFI was determined for every steer and rumen fluid was sampled using a transesophageal sampling device from the 10 most-efficient (Low-RFI) and the 10 least-efficient (High-RFI) steers within each breed. Rumen fluid samples were then subjected to 16S rRNA sequencing and a network-based systems biology analysis subsequently undertaken using PCIT incorporating the 16S sequencing data and individual RFI values across each breed and dietary phase. A total of 110 microbial taxa were connected (P < 0.05; r > 0.8) to the breed and diet contrasts examined; however, no single microbe was commonly connected to all contrasts. The Pyramidobacter genus was the most represented phylotype, displaying a positive connection with the Charolais steers during the grass silage diet, as well as a negative association with Charolais steers during the first high-concentrate diet and Holstein-Friesian steers during the zero-grazed grass diet. Similarly, of the 35 microbial taxa significantly connected to more than one breed/diet contrast, 12 displayed altered direction of association, indicating a differential relationship between the rumen microbiome and RFI phenotype depending on the prevailing dietary management. Acknowledgement: The animal model used in this study was funded by the Irish Department of Agriculture, Food and the Marine (RSF13/S/519). Kate Keogh received funding for this work from the Research Leaders 2025 program (co-funded by Teagasc and the European Union’s Horizon 2020, Marie Skłodowska-Curie grant agreement number 754380). [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

26. Additional file 1 of Bias, dispersion, and accuracy of genomic predictions for feedlot and carcase traits in Australian Angus steers

Author

Alexandre, Pâmela A., Li, Yutao, Hine, Brad C., Duff, Christian J., Ingham, Aaron B., Porto-Neto, Laercio R., and Reverter, Antonio

Abstract

Additional file 1: Table S1. Levels of sire linkage (negligible) across cohorts. The data provided represent the level of sire linkage across the year of birth cohorts used as validation population. Table S2. Breeding property linkages across cohorts. The data provided represent the breeding property linkages across the year of birth cohorts used as validation population. Table S3. Summary statistics for the genomic relationship matrix (GRM) values computed using Method 1 of VanRaden [29]. The data provided represent the summary statistics for the genomic relationship matrix (GRM) values computed using Method 1 of VanRaden [29]. Table S4. Accuracy (ACCT) of GEBV for feedlot and carcase traits from a 7-way cross-validation scheme based on YOB cohorts. The data provided represent the accuracy (computed from the correlation between GEBV and adjusted phenotypes in the validation population divided by the square root of heritability) of GEBV for feedlot and carcase traits from a 7-way cross-validation scheme based on year of birth cohorts used as validation population. Table S5. Estimates of GEBV bias using the LR method (BiasLR) for feedlot and carcase traits from a 7-way cross-validation scheme based on YOB cohorts. The data provided represent the estimates of GEBV bias using the LR method for feedlot and carcase traits from a 7-way cross-validation scheme based on year of birth cohorts used as validation population. Table S6. Estimates of GEBV dispersion using the LR method for feedlot and carcase traits from a 7-way cross-validation scheme based on YOB cohorts. The data provided represent the estimates of GEBV dispersion using the LR method (DispLR) for feedlot and carcase traits from a 7-way cross-validation scheme based on year of birth cohorts used as validation population. Table S7. Estimates of GEBV accuracy using the LR method (ACCLR) for feedlot and carcase traits from a 7-way cross-validation scheme based on YOB cohorts. The data provided represent the estimates of GEBV accuracy using the LR method for feedlot and carcase traits from a 7-way cross-validation scheme based on year of birth cohorts used as validation population.

Published
2021
Full Text
View/download PDF

27. Additional file 5 of Chromatin accessibility and regulatory vocabulary across indicine cattle tissues

Author

Alexandre, Pâmela A., Naval-Sánchez, Marina, Menzies, Moira, Nguyen, Loan T., Porto-Neto, Laercio R., Fortes, Marina R. S., and Reverter, Antonio

Subjects
endocrine system, nervous system, digestive, oral, and skin physiology, hormones, hormone substitutes, and hormone antagonists
Abstract

Additional file 5. Distribution of peaks by chromosome for muscle (A), liver (B) and hypothalamus (C).

Published
2021
Full Text
View/download PDF

35. Pooled genotyping strategies for the rapid construction of genomic reference populations()

Author

Alexandre, Pâmela, Porto-Neto, Laercio, Karaman, Emre, Lehnert, Sigrid, and Reverter, Antonio

Subjects
Male, Genotype, Animal Genetics and Genomics, Animals, Genetic Variation, Cattle, Female, Genomics, Breeding, Algorithms
Abstract

The growing concern with the environment is making important for livestock producers to focus on selection for efficiency-related traits, which is a challenge for commercial cattle herds due to the lack of pedigree information. To explore a cost-effective opportunity for genomic evaluations of commercial herds, this study compared the accuracy of bulls' genomic estimated breeding values (GEBV) using different pooled genotype strategies. We used ten replicates of previously simulated genomic and phenotypic data for one low (t1) and one moderate (t2) heritability trait of 200 sires and 2,200 progeny. Sire's GEBV were calculated using a univariate mixed model, with a hybrid genomic relationship matrix (h-GRM) relating sires to: 1) 1,100 pools of 2 animals; 2) 440 pools of 5 animals; 3) 220 pools of 10 animals; 4) 110 pools of 20 animals; 5) 88 pools of 25 animals; 6) 44 pools of 50 animals; and 7) 22 pools of 100 animals. Pooling criteria were: at random, grouped sorting by t1, grouped sorting by t2, and grouped sorting by a combination of t1 and t2. The same criteria were used to select 110, 220, 440, and 1,100 individual genotypes for GEBV calculation to compare GEBV accuracy using the same number of individual genotypes and pools. Although the best accuracy was achieved for a given trait when pools were grouped based on that same trait (t1: 0.50-0.56, t2: 0.66-0.77), pooling by one trait impacted negatively on the accuracy of GEBV for the other trait (t1: 0.25-0.46, t2: 0.29-0.71). Therefore, the combined measure may be a feasible alternative to use the same pools to calculate GEBVs for both traits (t1: 0.45-0.57, t2: 0.62-0.76). Pools of 10 individuals were identified as representing a good compromise between loss of accuracy (~10%-15%) and cost savings (~90%) from genotype assays. In addition, we demonstrated that in more than 90% of the simulations, pools present higher sires' GEBV accuracy than individual genotypes when the number of genotype assays is limited (i.e., 110 or 220) and animals are assigned to pools based on phenotype. Pools assigned at random presented the poorest results (t1: 0.07-0.45, t2: 0.14-0.70). In conclusion, pooling by phenotype is the best approach to implementing genomic evaluation using commercial herd data, particularly when pools of 10 individuals are evaluated. While combining phenotypes seems a promising strategy to allow more flexibility to the estimates made using pools, more studies are necessary in this regard.

Published
2019

39. Circulating leptin and its muscle gene expression in Nellore cattle with divergent feed efficiency

Author

Mota, Lúcio Flávio Macedo, primary, Bonafé, Cristina Moreira, additional, Alexandre, Pâmela Almeida, additional, Santana, Miguel Henrique, additional, Novais, Francisco José, additional, Toriyama, Erika, additional, Pires, Aldrin Vieira, additional, da Luz Silva, Saulo, additional, Leme, Paulo Roberto, additional, Ferraz, José Bento Sterman, additional, and Fukumasu, Heidge, additional

Published
2017
Full Text
View/download PDF

40. System biology approach to detect and assign biological functions and regulator genes to feed efficiency traits in Nellore cattle

Author

Alexandre, Pâmela, Kogelman, Lisette, Santana, Miguel, Eler, Joanir, Kadarmideen, Haja, and Fukumasu, Heidge

Abstract

The objective of this study was to use a system biology approach to identify biological mechanisms involved on feed efficiency in Nellore cattle and its possible regulator genes. Two modules of co-expressed and highly inter-connected genes correlated to feed efficiency were identified as well as five regulator genes.

Published
2014

42. Genome-wide association analysis of feed intake and residual feed intake in Nellore cattle

Author

Santana, Miguel HA, primary, Utsunomiya, Yuri T, additional, Neves, Haroldo HR, additional, Gomes, Rodrigo C, additional, Garcia, José F, additional, Fukumasu, Heidge, additional, Silva, Saulo L, additional, Oliveira Junior, Gerson A, additional, Alexandre, Pâmela A, additional, Leme, Paulo R, additional, Brassaloti, Ricardo A, additional, Coutinho, Luiz L, additional, Lopes, Thiago G, additional, Meirelles, Flávio V, additional, Eler, Joanir P, additional, and Ferraz, José BS, additional

Published
2014
Full Text
View/download PDF

45. Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep

Author

Marina, Héctor, Producción Animal, Marina, Héctor, Reverter, Antonio, Gutiérrez-Gil, Beatriz, Alexandre, Pâmela Almeida, Porto-Neto, Laercio R., Suárez-Vega, Aroa, Li, Yutao, Esteban-Blanco, Cristina, Arranz, Juan-José, Marina, Héctor, Producción Animal, Marina, Héctor, Reverter, Antonio, Gutiérrez-Gil, Beatriz, Alexandre, Pâmela Almeida, Porto-Neto, Laercio R., Suárez-Vega, Aroa, Li, Yutao, Esteban-Blanco, Cristina, and Arranz, Juan-José

Abstract

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual’s genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

46. Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep

Author

Producción Animal, Marina, Héctor, Reverter, Antonio, Gutiérrez-Gil, Beatriz, Alexandre, Pâmela Almeida, Porto-Neto, Laercio R., Suárez-Vega, Aroa, Li, Yutao, Esteban-Blanco, Cristina, Arranz, Juan-José, Producción Animal, Marina, Héctor, Reverter, Antonio, Gutiérrez-Gil, Beatriz, Alexandre, Pâmela Almeida, Porto-Neto, Laercio R., Suárez-Vega, Aroa, Li, Yutao, Esteban-Blanco, Cristina, and Arranz, Juan-José

Abstract

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual’s genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

47. Transcriptomic profile of Longissimus thoracis associated with fatty acid content in nellore cattle finished in feedlot

Author

Schettini, Gustavo Pimenta, Universidade Estadual Paulista (Unesp), Curi, Rogério Abdallah [UNESP], Baldi Rey, Fernando Sebastián [UNESP], de Lemos, Marcos Vinicius Antunes, and Alexandre, Pâmela Almeida

Subjects
Melhoramento genético, Ácidos graxos, Expressão gênica
Abstract

Submitted by Gustavo Pimenta Schettini (g.schettini@unesp.br) on 2021-08-02T20:06:17Z No. of bitstreams: 1 PERFIL TRANSCRIPTÔMICO DO MÚSCULO Longissimus thoracis ASSOCIADO A CONCENTRAÇÃO DE ÁCIDOS GRAXOS EM BOVINOS NELORE TERMINADOS EM CONFINAMENTO - GUSTAVO SCHETTINI - GMA.pdf: 1367863 bytes, checksum: 404042dcd1ca3537efa5ca1d81745009 (MD5) Rejected by Adriana Cristina Damato (adriana.damato@unesp.br), reason: Solicitamos que realize correções na submissão seguindo as orientações abaixo: 1 - Segundo a CAPES (Portaria nº 206, de 4 de setembro de 2018), o agradecimento deve conter exatamente a seguinte redação: O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Código de Financiamento 001. ( O código da CAPES será sempre 001) 2 Na submissão tem o número de processo da FAPESP? Se realmente vc recebeu bolsa da Fapesp também tem que colocar nos Agradecimentos da seguinte forma: -À Fundação de Amparo à Pesquisa do Estado de São Paulo – FAPESP, pelo auxílio financeiro para desenvolvimento desta pesquisa - NUMERO DO PROCESSO. Agradecemos a compreensão. on 2021-08-03T22:59:59Z (GMT) Submitted by Gustavo Pimenta Schettini (g.schettini@unesp.br) on 2021-08-03T23:08:19Z No. of bitstreams: 1 PERFIL TRANSCRIPTÔMICO DO MÚSCULO Longissimus thoracis ASSOCIADO A CONCENTRAÇÃO DE ÁCIDOS GRAXOS EM BOVINOS NELORE TERMINADOS EM CONFINAMENTO - GUSTAVO SCHETTINI - GMA.pdf: 1367863 bytes, checksum: 404042dcd1ca3537efa5ca1d81745009 (MD5) Rejected by Adriana Cristina Damato (adriana.damato@unesp.br), reason: Solicitamos que realize correções na submissão seguindo as orientações abaixo: 1-Gustavo vc precisa corrigir na página de Agradecimentos o agradecimento a CAPES que deve ser exatamente como te enviei. Segundo a CAPES (Portaria nº 206, de 4 de setembro de 2018), o agradecimento deve conter exatamente a seguinte redação: O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Código de Financiamento 001. (È necessário que seja essa mesma frase sem tirar nem por nada) 2-As palavras chaves devem ser adicionadas separadamente, uma por uma, com a inicial da primeira palavra em letra maiúscula e obrigatoriamente, 3 palavras em português OU 3 palavras em inglês RETIRADAS DO TESAURO DA UNESP. A Unesp tem um padrão de palavras-chave (TESAURO) e deve ser seguido. O intuito de um Tesauro é facilitar a recuperação de seu trabalho e "visibilidade científica", por isso, você deve representá-lo além das palavras de resumo. Acesso no endereço abaixo. tesaurounesp@unesp.br (Não encontrei nenhuma palavra chave da sua dissertação no TESAURO) 3- Na ficha catalográfica as palavras chaves devem ser escritas com a primeira letra de cada palavra em Maiúsculo. Favor corrigir. Se for palavra composta apenas a primeira letra da primeira palavra chave será Maiúscula. Ex: Nutrição animal 4- se vc fez sua pesquisa com animais vc precisa colocar o CEUA, Certificado do Comitê de Estica no Uso de Animais. Agradecemos a compreensão. on 2021-08-04T02:21:38Z (GMT) Submitted by Gustavo Pimenta Schettini (g.schettini@unesp.br) on 2021-08-04T10:57:02Z No. of bitstreams: 1 PERFIL TRANSCRIPTÔMICO DO MÚSCULO Longissimus thoracis ASSOCIADO A CONCENTRAÇÃO DE ÁCIDOS GRAXOS EM BOVINOS NELORE TERMINADOS EM CONFINAMENTO - GUSTAVO SCHETTINI - GMA.pdf: 1366073 bytes, checksum: 694e9e2cd1741ffb9677864b7a27da27 (MD5) Approved for entry into archive by Adriana Cristina Damato (adriana.damato@unesp.br) on 2021-08-04T12:33:32Z (GMT) No. of bitstreams: 1 schettini_gp_me_jabo.pdf: 1366073 bytes, checksum: 694e9e2cd1741ffb9677864b7a27da27 (MD5) Made available in DSpace on 2021-08-04T12:33:32Z (GMT). No. of bitstreams: 1 schettini_gp_me_jabo.pdf: 1366073 bytes, checksum: 694e9e2cd1741ffb9677864b7a27da27 (MD5) Previous issue date: 2021-07-08 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) A carne bovina possui alto valor nutricional por fornecer nutrientes fundamentais como os ácidos graxos (AG), unidades básicas dos lipídios, que participam de vias enzimáticas e regulatórias, do armazenamento energético e de funções estruturais, além de serem fatores importantes à aceitação do produto cárneo. Os ácidos graxos saturados (AGS) estão ligados a fatores de risco associados a cardiopatias e quadros inflamatórios, já os ácidos graxos mono- (AGMI) e poli-insaturados (AGPI), como os ácidos graxos essenciais (AGE) – ácidos linoleico (AL) e alfa-linolênico (ALA), condicionam proteção. O perfil de AG na carne bovina possui caráter complexo e poligênico. A partir do sequenciamento de ácidos nucléicos foi possível identificar genes diferencialmente expressos (GDE) em regiões genômicas associados à composição de AG na carne bovina. Contudo, poucas regiões genômicas explicaram grande parte das variâncias genéticas, e os GDE quando avaliados de forma isolada, não foram capazes de explicar totalmente o fenótipo e os mecanismos relacionados. Neste sentido, estudos de co-expressão (COE) e co-expressão diferencial (DCO) auxiliam nas análises de GDE, bem como os estudos de associação genômica ampla (GWAS). A análise de DCO é capaz de apontar genes e fatores de transcrição (FT) melhores conectados ao fenótipo, que, em associação com GDE e COE, fomentam o conhecimento relacionado à característica estudada. Desta forma, objetivou-se identificar e mensurar o perfil transcriptômico do perfil de AG no músculo Longissimus thoracis em bovinos da raça Nelore terminados em confinamento sob as abordagens de GDE, COE e DCO. Para a análise de COE foram utilizados dados de 44 touros, e destes, 30 com valores extremos para cada AG. Somas e razões (totalizando 14 fenótipos) foram utilizados nas análises de GDE e DCO. Para a análise de DCO, utilizou-se duas metodologias: (i) weighted gene co-expression network analysis (WGCNA) para cálculo da medida de conectividade diferencial (Kdiff) e (ii) partial correlation and information theory (PCIT). A metodologia PCIT foi utilizada somente para os grupos dos AGE com objetivo de identificar differential hubbing (DH) genes e FT com maior magnitude de regulatory impact factor. Um total de 912 GDE foram identificados, e os grupos de somas de AGPI (n=563) e ω-3 (n=346) foram os mais representativos. A análise de COE apontou três módulos, dos quais o módulo blue (n=1.776) foi correlacionado com oito dos 14 fenótipos de AG. Além disso, foram listados 759 genes DCO (WGCNA), com destaque para o ácido oleico (n=358) e a soma dos AGMI (n=120). Por meio da análise que combinou PCIT+WGCNA (DCO), os DH genes ASB5 e ERLIN1 e o FT NFIA se sobressaíram por impactarem ambos os AGE (AL e ALA). Além disso, os genes ELOVL5, FADS2, FASN e PPARG e os FT NFYA, NFYB e RORA foram atrelados a pelo menos um dos AGE. Ao confluir os resultados de GDE+COE+DCO (WGCNA) para todas os fenótipos, os genes ACSL3, ECI1, DECR2, FITM1 e SDHB foram sinalizados em pelo menos duas análises. Estes genes, relacionados ao metabolismo lipídico foram, até então, pouco explorados em estudos com bovinos. Estes achados contribuem para a melhor compreensão dos mecanismos genéticos subjacentes ao perfil de AG da carne em bovinos Nelore terminados em confinamento. Beef has high nutritional value for providing fundamental nutrients such as fatty acids (FA), basic units of lipids, which participate in enzymatic and regulatory pathways, energy storage, and structural functions, also being important factors for meat product acceptance. Saturated fatty acids (SFA) are linked to risk factors associated with heart disease and inflammatory conditions, whereas mono- (MUFA) and polyunsaturated (PUFA) fatty acids, such as essential fatty acids (EFA) – linoleic acid (LA), and alpha-linolenic (ALA), condition protection. The FA profile in beef has a complex and polygenic character. From the nucleic acids sequencing, it was possible to identify differentially expressed genes (DEG) and genomic regions associated with the FA composition in beef. However, few genomic regions explained a large part of the genetic variances, and the DEG evaluated in isolation was not able to fully explain the phenotype and the related mechanisms. In this sense, studies of co-expression (COE) and differential co-expression (DCO) help DEG analysis, as well as genomic wide association studies. DCO analysis can identify genes and transcription factors (TF) better connected to the phenotype, which, in association with DEG and COE, provide knowledge about the traits. Thus, the objective was to identify and measure the transcriptomic profile, under the DEG, COE, and DCO approach, of the FA profile in the Longissimus thoracis muscle of Nellore cattle finished in feedlot. For the COE analysis, data from 44 bulls were used, and of these, 30, with extreme values for each FA, sums, and ratios (totaling 14 phenotypes), were used in the DEG and DCO analyzes. For the DCO analysis were used two approaches, weighted gene co-expression network analysis (WGCNA) to calculate the differential connectivity measure (Kdiff) and partial correlation and information theory (PCIT) was used only for the EFA groups to identify differential hubbing (DH) genes and TF with a higher magnitude of regulatory impact factor. A total of 912 DEG were identified, and the PUFA sum (n = 563) and ω-3 sum (n = 346) were the most representative. The COE analysis indicated 19 modules, of which ten were related to all the traits evaluated. 759 DCO genes (WGCNA) were listed, with emphasis on oleic acid (n = 358) and MUFA sum (n = 120). On the other hand, through the analysis that combined PCIT + WGCNA (DCO), the DH genes ASB5 and ERLIN1 and TF NFIA stood out when impacting both EFA (LA and ALA), also the ELOVL5, FADS2, FASN, and PPARG genes and the TF NFYA, NFYB, and RORA linked to at least one EFA. When the results of DEG + COE + DCO (WGCNA) for all traits were combined, the ACSL3, ECI1, DECR2, FITM1 and SDHB genes were signaled in at least two analyzes. These genes, related to lipid metabolism, were, until then, little explored in cattle studies. These findings contribute to the understanding of the genetic mechanisms underlying the FA profile of Nellore cattle finished in feedlot. 001

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results