Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens

• Published in: Journal of animal breeding and genetics (1986) Vol. 131; no. 2; pp. 123 - 133
• Main Authors: Abdollahi‐Arpanahi, R, Nejati‐Javaremi, A, Pakdel, A, Moradi‐Shahrbabak, M, Morota, G, Valente, B.D, Kranis, A, Rosa, G.J.M, Gianola, D
• Format: Journal Article
• Language: English
• Published: Germany Blackwell Publishing Ltd 01.04.2014
• Subjects: Animals; Body Weight; breast muscle; Broiler chicken; broiler chickens; Chickens - genetics; Chickens - growth & development; Chickens - metabolism; egg production; Eggs; Female; Gene Frequency; Genetic markers; Genetic Markers - genetics; genome-enabled prediction; genomic best linear unbiased prediction; Genotype & phenotype; hens; Mammary Glands, Animal - metabolism; marker density; marker effect sizes; minor allele frequency; Muscles - metabolism; Phenotype; Polymorphism; Polymorphism, Single Nucleotide; Poultry; prediction; predictive ability; quantitative traits; single nucleotide polymorphism; predictive ability; minor allele frequency; genomic best linear unbiased prediction; Broiler chicken; marker density; marker effect sizes; genome-enabled prediction
• ISSN: 0931-2668; 1439-0388
• DOI: 10.1111/jbg.12075

The objective was to assess goodness of fit and predictive ability of subsets of single nucleotide polymorphism (SNP) markers constructed based on minor allele frequency (MAF), effect sizes and varying marker density. Target traits were body weight (BW), ultrasound measurement of breast muscle (BM) and hen house egg production (HHP) in broiler chickens. We used a 600 K Affymetrix platform with 1352 birds genotyped. The prediction method was genomic best linear unbiased prediction (GBLUP) with 354 564 single nucleotide polymorphisms (SNPs) used to derive a genomic relationship matrix (G). Predictive ability was assessed as the correlation between predicted genomic values and corrected phenotypes from a threefold cross‐validation. Predictive ability was 0.27 ± 0.002 for BW, 0.33 ± 0.001 for BM and 0.20 ± 0.002 for HHP. For the three traits studied, predictive ability decreased when SNPs with a higher MAF were used to construct G. Selection of the 20% SNPs with the largest absolute effect sizes induced a predictive ability equal to that from fitting all markers together. When density of markers increased from 5 K to 20 K, predictive ability enhanced slightly. These results provide evidence that designing a low‐density chip using low‐frequency markers with large effect sizes may be useful for commercial usage.