Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency

Y Lu, MJ Vandehaar, DM Spurlock, KA Weigel, LE Armentano, EE Connor, MP Coffey, RF Veerkamp, Y de Haas, CR Staples, Z Wang, MD Hanigan, RJ Tempelman

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3 Citations (Scopus)

Abstract

Genome-wide association (GWA) of feed efficiency (FE) could help target important genomic regions influencing FE. Data provided by an international dairy FE research consortium consisted of phenotypic records on dry matter intakes (DMI), milk energy (MILKE), and metabolic body weight (MBW) on 6,937 cows from 16 stations in 4 counties. Of these cows, 4,916 had genotypes on 57,347 single nucleotide polymorphism (SNP) markers. We compared a GWA analysis based on the more classical residual feed intake (RFI) model with one based on a previously proposed multiple trait (MT) approach for modeling FE using an alternative measure (DMI|MILKE,MBW). Both models were based on a single-step genomic BLUP procedure that allowed the use of phenotypes from both genotyped and nongenotyped cows. Estimated effects for single SNP markers were small and not statistically important but virtually identical for either FE measure (RFI vs. DMI|MILKE,MBW). However, upon further refining this analysis to develop joint tests within nonoverlapping 1-Mb windows, significant associations were detected between either measure of FE with a window on each of Bos taurus autosomes BTA12 and BTA26. There was, as expected, no overlap between detected genomic regions for DMI|MILKE,MBW and genomic regions influencing the energy sink traits (i.e., MILKE and MBW) because of orthogonal relationships clearly defined between the various traits. Conversely, GWA inferences on DMI can be demonstrated to be partly driven by genetic associations between DMI with these same energy sink traits, thereby having clear implications when comparing GWA studies on DMI to GWA studies on FE-like measures such as RFI.
Original languageEnglish
Pages (from-to)3140 - 3154
Number of pages15
JournalJournal of Dairy Science
Volume101
Issue number4
Early online date1 Feb 2018
DOIs
Publication statusFirst published - 1 Feb 2018

Fingerprint

dry matter intake
feed conversion
genome
energy
milk
body weight
genomics
feed intake
cows
single nucleotide polymorphism
autosomes
refining
dairies
phenotype
genotype
cattle
genome-wide association study
testing

Keywords

  • Feed efficiency
  • Genome-wide association
  • Multiple trait

Cite this

Lu, Y., Vandehaar, MJ., Spurlock, DM., Weigel, KA., Armentano, LE., Connor, EE., ... Tempelman, RJ. (2018). Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency. Journal of Dairy Science, 101(4), 3140 - 3154. https://doi.org/10.3168/jds.2017-13364
Lu, Y ; Vandehaar, MJ ; Spurlock, DM ; Weigel, KA ; Armentano, LE ; Connor, EE ; Coffey, MP ; Veerkamp, RF ; de Haas, Y ; Staples, CR ; Wang, Z ; Hanigan, MD ; Tempelman, RJ. / Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency. In: Journal of Dairy Science. 2018 ; Vol. 101, No. 4. pp. 3140 - 3154.
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abstract = "Genome-wide association (GWA) of feed efficiency (FE) could help target important genomic regions influencing FE. Data provided by an international dairy FE research consortium consisted of phenotypic records on dry matter intakes (DMI), milk energy (MILKE), and metabolic body weight (MBW) on 6,937 cows from 16 stations in 4 counties. Of these cows, 4,916 had genotypes on 57,347 single nucleotide polymorphism (SNP) markers. We compared a GWA analysis based on the more classical residual feed intake (RFI) model with one based on a previously proposed multiple trait (MT) approach for modeling FE using an alternative measure (DMI|MILKE,MBW). Both models were based on a single-step genomic BLUP procedure that allowed the use of phenotypes from both genotyped and nongenotyped cows. Estimated effects for single SNP markers were small and not statistically important but virtually identical for either FE measure (RFI vs. DMI|MILKE,MBW). However, upon further refining this analysis to develop joint tests within nonoverlapping 1-Mb windows, significant associations were detected between either measure of FE with a window on each of Bos taurus autosomes BTA12 and BTA26. There was, as expected, no overlap between detected genomic regions for DMI|MILKE,MBW and genomic regions influencing the energy sink traits (i.e., MILKE and MBW) because of orthogonal relationships clearly defined between the various traits. Conversely, GWA inferences on DMI can be demonstrated to be partly driven by genetic associations between DMI with these same energy sink traits, thereby having clear implications when comparing GWA studies on DMI to GWA studies on FE-like measures such as RFI.",
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Lu, Y, Vandehaar, MJ, Spurlock, DM, Weigel, KA, Armentano, LE, Connor, EE, Coffey, MP, Veerkamp, RF, de Haas, Y, Staples, CR, Wang, Z, Hanigan, MD & Tempelman, RJ 2018, 'Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency', Journal of Dairy Science, vol. 101, no. 4, pp. 3140 - 3154. https://doi.org/10.3168/jds.2017-13364

Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency. / Lu, Y; Vandehaar, MJ; Spurlock, DM; Weigel, KA; Armentano, LE; Connor, EE; Coffey, MP; Veerkamp, RF; de Haas, Y; Staples, CR; Wang, Z; Hanigan, MD; Tempelman, RJ.

In: Journal of Dairy Science, Vol. 101, No. 4, 01.02.2018, p. 3140 - 3154.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Lu, Y

AU - Vandehaar, MJ

AU - Spurlock, DM

AU - Weigel, KA

AU - Armentano, LE

AU - Connor, EE

AU - Coffey, MP

AU - Veerkamp, RF

AU - de Haas, Y

AU - Staples, CR

AU - Wang, Z

AU - Hanigan, MD

AU - Tempelman, RJ

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Lu Y, Vandehaar MJ, Spurlock DM, Weigel KA, Armentano LE, Connor EE et al. Genome-wide association analyses based on a multiple-trait approach for modeling feed efficiency. Journal of Dairy Science. 2018 Feb 1;101(4):3140 - 3154. https://doi.org/10.3168/jds.2017-13364