Indel detection from Whole Genome Sequencing data and association with lipid metabolism in pigs

PLoS One. 2019 Jun 27;14(6):e0218862. doi: 10.1371/journal.pone.0218862. eCollection 2019.

Abstract

The selection in commercial swine breeds for meat-production efficiency has been increasing among the past decades, reducing the intramuscular fat content, which has changed the sensorial and technological properties of pork. Through processes of natural adaptation and selective breeding, the accumulation of mutations has driven the genetic divergence between pig breeds. The most common and well-studied mutations are single-nucleotide polymorphisms (SNPs). However, insertions and deletions (indels) usually represents a fifth part of the detected mutations and should also be considered for animal breeding. In the present study, three different programs (Dindel, SAMtools mpileup, and GATK) were used to detect indels from Whole Genome Sequencing data of Iberian boars and Landrace sows. A total of 1,928,746 indels were found in common with the three programs. The VEP tool predicted that 1,289 indels may have a high impact on protein sequence and function. Ten indels inside genes related with lipid metabolism were genotyped in pigs from three different backcrosses with Iberian origin, obtaining different allelic frequencies on each backcross. Genome-Wide Association Studies performed in the Longissimus dorsi muscle found an association between an indel located in the C1q and TNF related 12 (C1QTNF12) gene and the amount of eicosadienoic acid (C20:2(n-6)).

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Female
  • Gene Frequency
  • Genome-Wide Association Study / veterinary*
  • Genomics
  • Genotyping Techniques / veterinary
  • High-Throughput Nucleotide Sequencing
  • INDEL Mutation*
  • Inbreeding
  • Lipid Metabolism*
  • Male
  • Muscle, Skeletal / chemistry
  • Swine
  • Whole Genome Sequencing / veterinary*

Grants and funding

This work was funded by the Ministerio de Economía y Competitividad (MINECO) and the Fondo Europeo de Desarrollo Regional (FEDER) projects AGL2014-56369-C2-2-R and AGL2017-82641-R. DCP was funded by a “Formació i Contractació de Personal Investigador Novell” (FI-DGR) Ph.D grant from the Generalitat de Catalunya (ECO/1788/2014). LCM was funded with a FPI grant from the AGL2014-56369-C2 project. MR was also funded by a FI-DGR (ECO/1639/2013). MB was financially supported by a “Ramón y Cajal” contract (RYC-2013-12573) from the Spanish Ministry of Economy and Competitiveness. We acknowledge the support of the Spanish Ministry of Economy and Competitiveness for the “Severo Ochoa Programme for Centres of Excellence in R&D” 2016-2019 (SEV-2015-0533) grant awarded to the Centre for Research in Agricultural Genomics and the CERCA Programme / Generalitat de Catalunya. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.