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Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits
BMC Genomics
  • Aline S. M. Cesar, Iowa State University
  • Luciana C. A. Regitano, Embrapa Pecuária Sudeste
  • James M. Reecy, Iowa State University
  • Mirele D. Poleti, University of São Paulo
  • Priscila S. N. Oliveira, Embrapa Pecuária Sudeste
  • Gabriella B. de Oliveira, University of São Paulo
  • Gabriel C. M. Moreira, University of São Paulo
  • Maurício A. Mudadu, Embrapa Informática Agropecuária
  • Polyana C Tizioto, University of São Paulo
  • James E. 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, Embrapa Pecuária Sudeste
  • Gerson B. Mourão, University of São Paulo
  • Adhemar Zerlotini, Embrapa Informática Agropecuária
  • Luiz L. Coutinho, University of São Paulo
Document Type
Article
Publication Version
Published Version
Publication Date
6-27-2018
DOI
10.1186/s12864-018-4871-y
Abstract

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.

Comments

This article is published as Cesar, Aline SM, Luciana CA Regitano, James M. Reecy, Mirele D. Poleti, Priscila SN Oliveira, Gabriella B. de Oliveira, Gabriel CM Moreira et al. "Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits." BMC genomics 19 (2018): 499. doi: 10.1186/s12864-018-4871-y.

Creative Commons License
Creative Commons Attribution 4.0 International
Copyright Owner
The Authors
Language
en
File Format
application/pdf
Citation Information
Aline S. M. Cesar, Luciana C. A. Regitano, James M. Reecy, Mirele D. Poleti, et al.. "Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits" BMC Genomics Vol. 19 (2018) p. 499
Available at: http://works.bepress.com/james_reecy/136/