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Genome-wide association studies for egg quality traits in White Leghorn layers using low-pass sequencing and SNP chip data.

Jinghui LiZigui WangDanny LubritzJesus ArangoJanet FultonPetek SettarKaylee RowlandHao ChengAnna Wolc
Published in: Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie (2022)
Low-pass sequencing data have been proposed as an alternative to single nucleotide polymorphism (SNP) chips in genome-wide association studies (GWAS) of several species. However, it has not been used in layer chickens yet. This study aims at comparing the GWAS results of White Leghorn chickens using low-pass sequencing data (1×) and 54 k SNP chip data. Ten commercially relevant egg quality traits including albumen height, shell strength, shell colour, egg weight and yolk weight collected from up to 1,420 White Leghorn chickens were analysed. The results showed that the genomic heritability estimates based on low-pass sequencing data were higher than those based on SNP chip data. Although two GWAS analyses showed similar overall landscape for most traits, low-pass sequencing captured some significant SNPs that were not on the SNP chip. In GWAS analysis using 54 k SNP chip data, after including more individuals (up to 5,700), additional significant SNPs not detected by low-pass sequencing data were found. In conclusion, GWAS using low-pass sequencing data showed similar results to those with SNP chip data and may require much larger sample sizes to show measurable advantages.
Keyphrases
  • genome wide
  • electronic health record
  • big data
  • single cell
  • high throughput
  • genome wide association
  • body mass index
  • physical activity
  • high density
  • machine learning
  • weight loss
  • copy number