Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

Duy Ngoc Do; L. L. G. Janss; Anders Bjerring Strathe; J. Jensen; Haja Kadarmideen

Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

Duy Ngoc Do, L. L. G. Janss, Anders Bjerring Strathe, J. Jensen, Haja Kadarmideen

Abstract

Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use of different power parameters had no effect on predictive ability. Partitioning of genomic variance showed that SNP groups either by position (intron, exon, downstream, upstream and 5’UTR) or by function (missense and protein-altering) had similar average explained variance per SNP, except that 3’UTR had a higher value.

Original language	English
Publication date	2014
Number of pages	3
Publication status	Published - 2014
Event	The 10th World Congress on Genetics Applied to Livestock Production - Vancouver, Canada Duration: 17 Aug 2014 → 22 Aug 2014

Conference

Conference	The 10th World Congress on Genetics Applied to Livestock Production
Country/Territory	Canada
City	Vancouver
Period	17/08/2014 → 22/08/2014

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Do, D. N., Janss, L. L. G., Strathe, A. B., Jensen, J., & Kadarmideen, H. (2014). Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models. Paper presented at The 10th World Congress on Genetics Applied to Livestock Production, Vancouver, Canada. https://asas.org/docs/default-source/wcgalp-proceedings-oral/124_paper_8968_manuscript_1400_0.pdf?sfvrsn=2

Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models. / Do, Duy Ngoc; Janss, L. L. G.; Strathe, Anders Bjerring et al.

2014. Paper presented at The 10th World Congress on Genetics Applied to Livestock Production, Vancouver, Canada.

Research output: Contribution to conference › Paper › Research › peer-review

Do, DN, Janss, LLG, Strathe, AB, Jensen, J & Kadarmideen, H 2014, 'Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models', Paper presented at The 10th World Congress on Genetics Applied to Livestock Production, Vancouver, Canada, 17/08/2014 - 22/08/2014. <https://asas.org/docs/default-source/wcgalp-proceedings-oral/124_paper_8968_manuscript_1400_0.pdf?sfvrsn=2>

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title = "Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models",

abstract = "Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use of different power parameters had no effect on predictive ability. Partitioning of genomic variance showed that SNP groups either by position (intron, exon, downstream, upstream and 5{\textquoteright}UTR) or by function (missense and protein-altering) had similar average explained variance per SNP, except that 3{\textquoteright}UTR had a higher value. ",

author = "Do, {Duy Ngoc} and Janss, {L. L. G.} and Strathe, {Anders Bjerring} and J. Jensen and Haja Kadarmideen",

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note = "The 10th World Congress on Genetics Applied to Livestock Production ; Conference date: 17-08-2014 Through 22-08-2014",

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T1 - Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

AU - Do, Duy Ngoc

AU - Janss, L. L. G.

AU - Strathe, Anders Bjerring

AU - Jensen, J.

AU - Kadarmideen, Haja

PY - 2014

Y1 - 2014

N2 - Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use of different power parameters had no effect on predictive ability. Partitioning of genomic variance showed that SNP groups either by position (intron, exon, downstream, upstream and 5’UTR) or by function (missense and protein-altering) had similar average explained variance per SNP, except that 3’UTR had a higher value.

AB - Improvement of feed efficiency is essential in pig breeding and selection for reduced residual feed intake (RFI) is an option. The study applied Bayesian Power LASSO (BPL) models with different power parameter to investigate genetic architecture, to predict genomic breeding values, and to partition genomic variance for RFI and daily feed intake (DFI). A total of 1272 Duroc pigs had both genotypic and phenotypic records for these traits. Significant SNPs were detected on chromosome 1 (SSC 1) and SSC 14 for RFI and on SSC 1 for DFI. BPL models had similar accuracy and bias as GBLUP method but use of different power parameters had no effect on predictive ability. Partitioning of genomic variance showed that SNP groups either by position (intron, exon, downstream, upstream and 5’UTR) or by function (missense and protein-altering) had similar average explained variance per SNP, except that 3’UTR had a higher value.

M3 - Paper

T2 - The 10th World Congress on Genetics Applied to Livestock Production

Y2 - 17 August 2014 through 22 August 2014

ER -

Genomic prediction and genomic variance partitioning of daily and residual feed intake in pigs using Bayesian Power Lasso models

Abstract

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