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Comparing BeadChip and WGS Genotyping: Non-Technical Failed Calling Is Attributable to Additional Variation within
Moran Gershoni1, Andrey Shirak1, Rotem Raz1
1Agricultural Research Organization (ARO), Volcani Center, Institute of Animal Science, HaMaccabim Road, P.O. Box 15159, Rishon LeTsiyon 7528809, Israel.
Genes
|March 25, 2022
Summary
Whole-genome sequencing (WGS) offers higher accuracy than microarray genotyping in dairy cattle. WGS can resolve errors and potentially explain missing heritability in genomic selection for economically important traits.
Area of Science:
- Animal Genetics
- Genomic Selection
- Dairy Cattle Breeding
Background:
- Microarray-based genomic selection is crucial for improving dairy cattle traits but is limited by incomplete heritability explanation.
- Genotype data accuracy is key to maximizing genetic gain in livestock.
Purpose of the Study:
- To compare genotyping accuracy between whole-genome sequencing (WGS) and microarray techniques in Israeli Holstein bulls.
- To identify sources of error in microarray genotyping and assess WGS's potential to resolve them.
Main Methods:
- Compared WGS data with Illumina BovineSNP50 BeadChip genotypes using the GATK pipeline.
- Analyzed short-variant discovery and assessed discrepancies in variable regions near SNPs.
- Evaluated an alternative method mimicking microarray hybridization.
Main Results:
- Low mismatch rate (0.2%) between BeadChip and WGS genotypes.
- Significant extra variation (40% of SNPs) near targeted sites interfered with BeadChip hybridization.
- BeadChip introduced systematic genotyping errors (null allele-like effects, Mendelian errors), which GATK resolved using local haplotype assembly.
Conclusions:
- Microarray designs should avoid polymorphic regions with high extra variation.
- WGS data can correct erroneous microarray genotyping, potentially addressing the missing heritability issue in dairy cattle genomic selection.
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