Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness

The aim of this study was to identify single nucleotide polymorphisms (SNPs) that could be associated with back fat thickness (BFT) in pigs. To achieve this goal, we evaluated the potential and limits of an experimental design that combined several methodologies. DNA samples from two groups of Itali...

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Main Authors: Samuele Bovo, Francesca Bertolini, Giuseppina Schiavo, Gianluca Mazzoni, Stefania Dall’Olio, Luca Fontanesi
Format: Article
Language:English
Published: Wiley 2015-01-01
Series:International Journal of Genomics
Online Access:http://dx.doi.org/10.1155/2015/950737
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author Samuele Bovo
Francesca Bertolini
Giuseppina Schiavo
Gianluca Mazzoni
Stefania Dall’Olio
Luca Fontanesi
author_facet Samuele Bovo
Francesca Bertolini
Giuseppina Schiavo
Gianluca Mazzoni
Stefania Dall’Olio
Luca Fontanesi
author_sort Samuele Bovo
collection DOAJ
description The aim of this study was to identify single nucleotide polymorphisms (SNPs) that could be associated with back fat thickness (BFT) in pigs. To achieve this goal, we evaluated the potential and limits of an experimental design that combined several methodologies. DNA samples from two groups of Italian Large White pigs with divergent estimating breeding value (EBV) for BFT were separately pooled and sequenced, after preparation of reduced representation libraries (RRLs), on the Ion Torrent technology. Taking advantage from SNAPE for SNPs calling in sequenced DNA pools, 39,165 SNPs were identified; 1/4 of them were novel variants not reported in dbSNP. Combining sequencing data with Illumina PorcineSNP60 BeadChip genotyping results on the same animals, 661 genomic positions overlapped with a good approximation of minor allele frequency estimation. A total of 54 SNPs showing enriched alleles in one or in the other RRLs might be potential markers associated with BFT. Some of these SNPs were close to genes involved in obesity related phenotypes.
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institution Kabale University
issn 2314-436X
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language English
publishDate 2015-01-01
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series International Journal of Genomics
spelling doaj-art-19137864863f4f7ca1fca59e2201a3be2025-02-03T06:42:14ZengWileyInternational Journal of Genomics2314-436X2314-43782015-01-01201510.1155/2015/950737950737Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat ThicknessSamuele Bovo0Francesca Bertolini1Giuseppina Schiavo2Gianluca Mazzoni3Stefania Dall’Olio4Luca Fontanesi5Department of Agricultural and Food Sciences (DISTAL), Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, ItalyDepartment of Agricultural and Food Sciences (DISTAL), Division of Animal Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, ItalyThe aim of this study was to identify single nucleotide polymorphisms (SNPs) that could be associated with back fat thickness (BFT) in pigs. To achieve this goal, we evaluated the potential and limits of an experimental design that combined several methodologies. DNA samples from two groups of Italian Large White pigs with divergent estimating breeding value (EBV) for BFT were separately pooled and sequenced, after preparation of reduced representation libraries (RRLs), on the Ion Torrent technology. Taking advantage from SNAPE for SNPs calling in sequenced DNA pools, 39,165 SNPs were identified; 1/4 of them were novel variants not reported in dbSNP. Combining sequencing data with Illumina PorcineSNP60 BeadChip genotyping results on the same animals, 661 genomic positions overlapped with a good approximation of minor allele frequency estimation. A total of 54 SNPs showing enriched alleles in one or in the other RRLs might be potential markers associated with BFT. Some of these SNPs were close to genes involved in obesity related phenotypes.http://dx.doi.org/10.1155/2015/950737
spellingShingle Samuele Bovo
Francesca Bertolini
Giuseppina Schiavo
Gianluca Mazzoni
Stefania Dall’Olio
Luca Fontanesi
Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness
International Journal of Genomics
title Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness
title_full Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness
title_fullStr Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness
title_full_unstemmed Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness
title_short Reduced Representation Libraries from DNA Pools Analysed with Next Generation Semiconductor Based-Sequencing to Identify SNPs in Extreme and Divergent Pigs for Back Fat Thickness
title_sort reduced representation libraries from dna pools analysed with next generation semiconductor based sequencing to identify snps in extreme and divergent pigs for back fat thickness
url http://dx.doi.org/10.1155/2015/950737
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