Dentificación de variantes génicas expresadas mediante RNA-Seq en cerdos con fenotipos divergentes para crecimiento y engrasamiento

• A.M. Martínez ^[1] ; D. Perez Montarelo ^[1] ; C. Rodriguez ^[1] ; N. Ibañez ^[2] ; J.M. Folch ^[3] ; L. Silió ^[3] ; E. Alves ^[3] ; A.I. Fernández ^[3]
  1. [1] Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria

     Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria

     Madrid, España

     
  2. [2] Institut de Recerca i Tecnologia Agroalimentaries

     Institut de Recerca i Tecnologia Agroalimentaries

     Barcelona, España

     
  3. [3] Centre de Recerca Agrigenómica

     Centre de Recerca Agrigenómica

     Barcelona, España

     

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• Localización: XV Jornadas sobre Producción Animal: 14 y 15 de mayo de 2013, Zaragoza / Jorge Hugo Calvo Lacosta (aut.), Isabel Casasús Pueyo (aut.), Margalida Joy Torrens (aut.), Javier Álvarez Rodríguez (aut.), Luis Varona Aguado (aut.), Begoña Panea Doblado (aut.), Carlos Calvete Margolles (aut.), Joaquim Barcells Teres (aut.), Vol. 2, 2013, ISBN 978-84-695-7684-7, págs. 571-573
• Idioma: español
• Títulos paralelos:
  • Identification of expressed gene variants by RNA-Seq in pigs phenotipically divergent for growth and fatness
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  • Texto Completo Libro  1 (pdf)   2 (pdf) 
• Resumen

  • The RNA-Seq technique is not only a great tool for transcriptome characterization and gene expression analyses, but also a powerful tool for analyzing genome variations such as SNVs. In this study we have identified SNPs using RNA-Seq data from liver and hypothalamus samples of two groups of pigs showing divergent phenotypes for growth and fatness coming from an Iberian x Landrace backcross. We have identified more than 83,000 SNPs segregating in these animals. Among them, 10,064 and 8,962 SNPs in hypothalamus and liver, respectively, are potentially informative for further analyses. The distribution of the SNPs along pig chromosomes revealed some interesting data, such as for chromosomes 1, 7, 10, 11 and 14 where the number of informative SNPs differed from the expected. Among the genes carrying the detected informative SNPs highlight FGF1, VCAM1, AGL and JAK1 as powerful biological and positional candidate genes to underlay the QTL for growth and fatness identified in previous studies.