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

R. Abdollahi-Arpanahi, A. Nejati-Javaremi, A. Pakdel, M. Moradi-Shahrbabak, G. Morota, B. D. Valente, A. Kranis, G. J.M. Rosa, D. Gianola

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)123-133
Number of pages11
JournalJournal of Animal Breeding and Genetics
Volume131
Issue number2
DOIs
StatePublished - Apr 1 2014

Fingerprint

quantitative traits
Gene Frequency
single nucleotide polymorphism
gene frequency
Single Nucleotide Polymorphism
Chickens
chickens
prediction
breast muscle
genomics
Ovum
egg production
hens
Breast
Body Weight
Muscles
body weight
Birds
broiler chickens
Phenotype

Keywords

  • Broiler chicken
  • Genome-enabled prediction
  • Genomic best linear unbiased prediction
  • Marker density
  • Marker effect sizes
  • Minor allele frequency
  • Predictive ability

ASJC Scopus subject areas

  • Food Animals
  • Animal Science and Zoology

Cite this

Abdollahi-Arpanahi, R., Nejati-Javaremi, A., Pakdel, A., Moradi-Shahrbabak, M., Morota, G., Valente, B. D., ... Gianola, D. (2014). Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens. Journal of Animal Breeding and Genetics, 131(2), 123-133. https://doi.org/10.1111/jbg.12075

Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens. / Abdollahi-Arpanahi, R.; Nejati-Javaremi, A.; Pakdel, A.; Moradi-Shahrbabak, M.; Morota, G.; Valente, B. D.; Kranis, A.; Rosa, G. J.M.; Gianola, D.

In: Journal of Animal Breeding and Genetics, Vol. 131, No. 2, 01.04.2014, p. 123-133.

Research output: Contribution to journalArticle

Abdollahi-Arpanahi, R, Nejati-Javaremi, A, Pakdel, A, Moradi-Shahrbabak, M, Morota, G, Valente, BD, Kranis, A, Rosa, GJM & Gianola, D 2014, 'Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens', Journal of Animal Breeding and Genetics, vol. 131, no. 2, pp. 123-133. https://doi.org/10.1111/jbg.12075
Abdollahi-Arpanahi, R. ; Nejati-Javaremi, A. ; Pakdel, A. ; Moradi-Shahrbabak, M. ; Morota, G. ; Valente, B. D. ; Kranis, A. ; Rosa, G. J.M. ; Gianola, D. / Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens. In: Journal of Animal Breeding and Genetics. 2014 ; Vol. 131, No. 2. pp. 123-133.
@article{e732d5ba237f4cba8bb5a62cd5c5ce93,
title = "Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens",
abstract = "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.",
keywords = "Broiler chicken, Genome-enabled prediction, Genomic best linear unbiased prediction, Marker density, Marker effect sizes, Minor allele frequency, Predictive ability",
author = "R. Abdollahi-Arpanahi and A. Nejati-Javaremi and A. Pakdel and M. Moradi-Shahrbabak and G. Morota and Valente, {B. D.} and A. Kranis and Rosa, {G. J.M.} and D. Gianola",
year = "2014",
month = "4",
day = "1",
doi = "10.1111/jbg.12075",
language = "English (US)",
volume = "131",
pages = "123--133",
journal = "Journal of Animal Breeding and Genetics",
issn = "0931-2668",
publisher = "Wiley-Blackwell",
number = "2",

}

TY - JOUR

T1 - Effect of allele frequencies, effect sizes and number of markers on prediction of quantitative traits in chickens

AU - Abdollahi-Arpanahi, R.

AU - Nejati-Javaremi, A.

AU - Pakdel, A.

AU - Moradi-Shahrbabak, M.

AU - Morota, G.

AU - Valente, B. D.

AU - Kranis, A.

AU - Rosa, G. J.M.

AU - Gianola, D.

PY - 2014/4/1

Y1 - 2014/4/1

N2 - 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.

AB - 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.

KW - Broiler chicken

KW - Genome-enabled prediction

KW - Genomic best linear unbiased prediction

KW - Marker density

KW - Marker effect sizes

KW - Minor allele frequency

KW - Predictive ability

UR - http://www.scopus.com/inward/record.url?scp=84897635147&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897635147&partnerID=8YFLogxK

U2 - 10.1111/jbg.12075

DO - 10.1111/jbg.12075

M3 - Article

C2 - 24397350

AN - SCOPUS:84897635147

VL - 131

SP - 123

EP - 133

JO - Journal of Animal Breeding and Genetics

JF - Journal of Animal Breeding and Genetics

SN - 0931-2668

IS - 2

ER -