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Registro Completo |
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Biblioteca(s): |
Embrapa Agropecuária Oeste. |
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Data corrente: |
23/07/2003 |
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Data da última atualização: |
23/07/2003 |
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Autoria: |
MIRANDA, E. E. de. (Coord.). |
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Título: |
Coleção Brasil Visto do Espaço: Bahia. |
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Ano de publicação: |
2000 |
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Fonte/Imprenta: |
Campinas: Embrapa Monitoramento por Satélite; Brasília: Embrapa Comunicação para Transferência de Tecnologia, [2000?]. |
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Descrição Física: |
1 CD-ROM. |
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ISBN: |
85-7383-131-6 |
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Idioma: |
Português |
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Palavras-Chave: |
Bahia; Brasil. |
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Thesagro: |
Sensoriamento Remoto. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00509nam a2200157 a 4500
001 1245790
005 2003-07-23
008 2000 bl uuuu 0 #d
020 $a85-7383-131-6
100 1 $aMIRANDA, E. E. de. (Coord.).
245 $aColeção Brasil Visto do Espaço$bBahia.
260 $aCampinas: Embrapa Monitoramento por Satélite; Brasília: Embrapa Comunicação para Transferência de Tecnologia, [2000?].$c2000
300 $c1 CD-ROM.
650 $aSensoriamento Remoto
653 $aBahia
653 $aBrasil
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Registro original: |
Embrapa Agropecuária Oeste (CPAO) |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Pecuária Sudeste. |
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Data corrente: |
20/12/2018 |
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Data da última atualização: |
19/02/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
CESAR, A. S. M.; REGITANO, L. C. de A.; REECY, J. M.; POLETI, M. D.; OLIVEIRA, P. S. N. de; OLIVEIRA, G. B. de; MOREIRA, G. C. M.; MUDADU, M. de A.; TIZIOTO, P. L.; KOLTES, J. E.; Fritz-Waters, E.; KRAMER, L.; GARRICK, D.; BEIKI, H.; GEISTLINGER, L.; MOURÃO, G. B.; ZERLOTINI NETO, A.; COUTINHO, L. L. |
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Afiliação: |
ALINE S. M. CESAR, USP, Iowa State University; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE; JAMES M. REECY, Iowa State University; MIRELE D. POLETI, USP; Priscila Silva Neubern de Oliveira, Bolsista/Embrapa Pecuária Sudeste; GABRIELLA B. DE OLIVEIRA, USP; GABRIEL C. M. MOREIRA, USP; MAURICIO DE ALVARENGA MUDADU, CNPTIA; POLYANA C. TIZIOTO, USP; JAMES EUGENE KOLTES, Iowa State University; Elyn Fritz-Waters, Iowa State University; LUKE KRAMER, Iowa State University; DORIAN GARRICK, Massey University; HAMID BEIKI, Iowa State University; LUDWIG GEISTLINGER, Bolsista/Embrapa Pecuária Sudeste; GERSON B. MOURÃO, USP; ADHEMAR ZERLOTINI NETO, CNPTIA; Luiz Lehmann Coutinho, USP. |
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Título: |
Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
BMC Genomics, v. 19, p. 1-20, 2018. |
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DOI: |
https://doi.org/10.1186/s12864-018-4871-y |
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Idioma: |
Inglês |
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Notas: |
Article number: 499. Na publicação: Luciana C. A. Regitano, Maurício A. Mudadu, Adhemar Zerlotini. |
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Conteúdo: |
Background: Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits. Results: We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism. Conclusion: This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals. MenosBackground: Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits. Results: We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in l... Mostrar Tudo |
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Palavras-Chave: |
Ácidos graxos; Doenças metabólicas; EQTL; Expressão gênica; Expression quantitative trait loci. |
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Thesaurus NAL: |
Fatty acids; Gene expression; Mammals; Metabolic diseases. |
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Categoria do assunto: |
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L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/189052/1/AP-Identification-Cesar-etal.pdf
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Marc: |
LEADER 03558naa a2200457 a 4500
001 2106227
005 2019-02-19
008 2018 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1186/s12864-018-4871-y$2DOI
100 1 $aCESAR, A. S. M.
245 $aIdentification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.$h[electronic resource]
260 $c2018
500 $aArticle number: 499. Na publicação: Luciana C. A. Regitano, Maurício A. Mudadu, Adhemar Zerlotini.
520 $aBackground: Integration of high throughput DNA genotyping and RNA-sequencing data allows for the identification of genomic regions that control gene expression, known as expression quantitative trait loci (eQTL), on a whole genome scale. Intramuscular fat (IMF) content and carcass composition play important roles in metabolic and physiological processes in mammals because they influence insulin sensitivity and consequently prevalence of metabolic diseases such as obesity and type 2 diabetes. However, limited information is available on the genetic variants and mechanisms associated with IMF deposition in mammals. Thus, our hypothesis was that eQTL analyses could identify putative regulatory regions and transcription factors (TFs) associated with intramuscular fat (IMF) content traits. Results: We performed an integrative eQTL study in skeletal muscle to identify putative regulatory regions and factors associated with intramuscular fat content traits. Data obtained from skeletal muscle samples of 192 animals was used for association analysis between 461,466 SNPs and the transcription level of 11,808 genes. This yielded 1268 cis- and 10,334 trans-eQTLs, among which we identified nine hotspot regions that each affected the expression of > 119 genes. These putative regulatory regions overlapped with previously identified QTLs for IMF content. Three of the hotspots respectively harbored the transcription factors USF1, EGR4 and RUNX1T1, which are known to play important roles in lipid metabolism. From co-expression network analysis, we further identified modules significantly correlated with IMF content and associated with relevant processes such as fatty acid metabolism, carbohydrate metabolism and lipid metabolism. Conclusion: This study provides novel insights into the link between genotype and IMF content as evident from the expression level. It thereby identifies genomic regions of particular importance and associated regulatory factors. These new findings provide new knowledge about the biological processes associated with genetic variants and mechanisms associated with IMF deposition in mammals.
650 $aFatty acids
650 $aGene expression
650 $aMammals
650 $aMetabolic diseases
653 $aÁcidos graxos
653 $aDoenças metabólicas
653 $aEQTL
653 $aExpressão gênica
653 $aExpression quantitative trait loci
700 1 $aREGITANO, L. C. de A.
700 1 $aREECY, J. M.
700 1 $aPOLETI, M. D.
700 1 $aOLIVEIRA, P. S. N. de
700 1 $aOLIVEIRA, G. B. de
700 1 $aMOREIRA, G. C. M.
700 1 $aMUDADU, M. de A.
700 1 $aTIZIOTO, P. L.
700 1 $aKOLTES, J. E.
700 1 $aFritz-Waters, E.
700 1 $aKRAMER, L.
700 1 $aGARRICK, D.
700 1 $aBEIKI, H.
700 1 $aGEISTLINGER, L.
700 1 $aMOURÃO, G. B.
700 1 $aZERLOTINI NETO, A.
700 1 $aCOUTINHO, L. L.
773 $tBMC Genomics$gv. 19, p. 1-20, 2018.
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