title: Comparison of whole-genome (13X) and capture (87X) resequencing methods for SNP and genotype callings.
abstract: The number of polymorphisms identified with next-generation sequencing approaches depends directly on the sequencing depth and therefore on the experimental cost. Although higher levels of depth ensure more sensitive and more specific SNP calls, economic constraints limit the increase of depth for whole-genome resequencing (WGS). For this reason, capture resequencing is used for studies focusing on only some specific regions of the genome. However, several biases in capture resequencing are known to have a negative impact on the sensitivity of SNP detection. Within this framework, the aim of this study was to compare the accuracy of WGS and capture resequencing on SNP detection and genotype calling, which differ in terms of both sequencing depth and biases. Indeed, we have evaluated the SNP calling and genotyping accuracy in a WGS dataset (13X) and in a capture resequencing dataset (87X) performed on 11 individuals. The percentage of SNPs not identified due to a sevenfold sequencing depth decrease was estimated at 7.8% using a down-sampling procedure on the capture sequencing dataset. A comparison of the 87X capture sequencing dataset with the WGS dataset revealed that capture-related biases were leading with the loss of 5.2% of SNPs detected with WGS. Nevertheless, when considering the SNPs detected by both approaches, capture sequencing appears to achieve far better SNP genotyping, with about 4.4% of the WGS genotypes that can be considered as erroneous and even 10% focusing on heterozygous genotypes. In conclusion, WGS and capture deep sequencing can be considered equivalent strategies for SNP detection, as the rate of SNPs not identified because of a low sequencing depth in the former is quite similar to SNPs missed because of method biases of the latter. On the other hand, capture deep sequencing clearly appears more adapted for studies requiring great accuracy in genotyping.
authors.affiliation: INRA, UMR1348 PEGASE, Saint-Gilles, F-35590, France; Agrocampus Ouest, UMR1348 PEGASE, Rennes, F-35000, France; Université Européenne de Bretagne, Rennes, France.
authors.forename: P F
authors.initials: PF
authors.lastname: Roux
authors.forename: S
authors.initials: S
authors.lastname: Marthey
authors.forename: A
authors.initials: A
authors.lastname: Djari
authors.forename: M
authors.initials: M
authors.lastname: Moroldo
authors.forename: D
authors.initials: D
authors.lastname: Esquerré
authors.forename: J
authors.initials: J
authors.lastname: Estellé
authors.forename: C
authors.initials: C
authors.lastname: Klopp
authors.forename: S
authors.initials: S
authors.lastname: Lagarrigue
authors.forename: O
authors.initials: O
authors.lastname: Demeure
mesh_terms: D000818:Animals; D002645:Chickens / Q000235:genetics; D016678:Genome; D005838:Genotype; D060005:Genotyping Techniques / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D017422:Sequence Analysis, DNA / Q000379:methods*
keywords: SNP calling; genotype calling; next-generation sequencing; sequencing depth; single nucleotide polymorphism