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High-throughput and Cost-effective Chicken Genotyping Using Next-Generation Sequencing

Pértille, Fábio (författare)
Guerrero-Bosagna, Carlos (författare)
da Silva, Vinicius Henrique (författare)
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Boschiero, Clarissa (författare)
da Silva Nunes, José de Ribamar (författare)
Corrêa Ledur, Mônica (författare)
Jensen, Per (författare)
Lehmann Coutinho, Luiz (författare)
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 (utgivare)
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Nature Publishing Group 2016
2016
Engelska.
Ingår i: Scientific Reports. - 2045-2322. ; 6
  • swepub:Mat__t
Abstract Ämnesord
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  • Chicken genotyping is becoming common practice in conventional animal breeding improvement.Despite the power of high-throughput methods for genotyping, their high cost limits large scale use inanimal breeding and selection. In the present paper we optimized the CornellGBS, an efficient and costeffectivegenotyping by sequence approach developed in plants, for its application in chickens. Herewe describe the successful genotyping of a large number of chickens (462) using CornellGBS approach.Genomic DNA was cleaved with the PstI enzyme, ligated to adapters with barcodes identifyingindividual animals, and then sequenced on Illumina platform. After filtering parameters were applied,134,528 SNPs were identified in our experimental population of chickens. Of these SNPs, 67,096 hada minimum taxon call rate of 90% and were considered ‘unique tags’. Interestingly, 20.7% of theseunique tags have not been previously reported in the dbSNP. Moreover, 92.6% of these SNPs wereconcordant with a previous Whole Chicken-genome re-sequencing dataset used for validation purposes.The application of CornellGBS in chickens showed high performance to infer SNPs, particularly inexonic regions and microchromosomes. This approach represents a cost-effective (~US$50/sample)and powerful alternative to current genotyping methods, which has the potential to improve wholegenomeselection (WGS), and genome-wide association studies (GWAS) in chicken production.

Ämnesord

Natural Sciences  (hsv)
Computer and Information Science  (hsv)
Bioinformatics (Computational Biology)  (hsv)
Naturvetenskap  (hsv)
Data- och informationsvetenskap  (hsv)
Bioinformatik (beräkningsbiologi)  (hsv)

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