Study on the concordance between different SNP‐genotyping platforms in sheep

Abstract

Different SNP genotyping technologies are commonly used in multiple studies to perform QTL detection, genotype imputation, and genomic predictions. Therefore, genotyping errors cannot be ignored, as they can reduce the accuracy of different procedures applied in genomic selection, such as genomic imputation, genomic predictions, and false-positive results in genome-wide association studies. Currently, whole-genome resequencing (WGR) also offers the potential for variant calling analysis and high-throughput genotyping. WGR might overshadow array-based genotyping technologies due to the larger amount and precision of the genomic information provided; however, its comparatively higher price per individual still limits its use in larger populations. Thus, the objective of this work was to evaluate the accuracy of the two most popular SNP-chip technologies, namely, Affymetrix and Illumina, for high-throughput genotyping in sheep considering high-coverage WGR datasets as references. Analyses were performed using two reference sheep genome assemblies, the popular Oar_v3.1 reference genome and the latest available version Oar_rambouillet_v1.0. Our results demonstrate that the genotypes from both platforms are suggested to have high concordance rates with the genotypes determined from reference WGR datasets (96.59% and 99.51% for Affymetrix and Illumina technologies, respectively). The concordance results provided in the current study can pinpoint low reproducible markers across multiple platforms used for sheep genotyping data. Comparing results using two reference genome assemblies also informs how genome assembly quality can influence genotype concordance rates among different genotyping platforms. Moreover, we describe an efficient pipeline to test the reliability of markers included in sheep SNP-chip panels against WGR datasets available on public databases. This pipeline may be helpful for discarding low-reliability markers before exploiting genomic information for gene mapping analyses or genomic prediction.

Using whole genome sequence to compare variant callers and breed differences of US sheep

“…Berry and others used genotypes from 89 sheep to compare two 50K SNP bead arrays and showed the genotypes were 98% concordant between the two bead arrays, showing that both bead arrays were comparable ( Berry et al, 2016 ). Another study with 31 sheep compared two 50K SNP bead arrays and SNPs identified from WGS analyzed with GATK v4.0 ( Marina et al, 2021 ). They identified similar concordance between the two arrays, 98.8% and slightly lower concordance (95.51%–97.65%) to the genotyping from WGS data ( Marina et al, 2021 ).…”

“…Another study with 31 sheep compared two 50K SNP bead arrays and SNPs identified from WGS analyzed with GATK v4.0 ( Marina et al, 2021 ). They identified similar concordance between the two arrays, 98.8% and slightly lower concordance (95.51%–97.65%) to the genotyping from WGS data ( Marina et al, 2021 ). However, neither study looks at the differences between which variant caller is utilized for analyzing WGS.…”