Genomic prediction using QTL derived from whole genome sequence data

Research output: Contribution to conferencePaperResearchpeer-review

Standard

Genomic prediction using QTL derived from whole genome sequence data. / Brøndum, Rasmus Froberg; Su, Guosheng; Janss, Luc; Sahana, Goutam; Lund, Mogens Sandø.

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

Research output: Contribution to conferencePaperResearchpeer-review

Harvard

Brøndum, RF, Su, G, Janss, L, Sahana, G & Lund, MS 2014, 'Genomic prediction using QTL derived from whole genome sequence data', Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada, 17/08/2014 - 22/08/2014.

APA

Brøndum, R. F., Su, G., Janss, L., Sahana, G., & Lund, M. S. (2014). Genomic prediction using QTL derived from whole genome sequence data. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada.

CBE

Brøndum RF, Su G, Janss L, Sahana G, Lund MS. 2014. Genomic prediction using QTL derived from whole genome sequence data. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada.

MLA

Brøndum, Rasmus Froberg et al. Genomic prediction using QTL derived from whole genome sequence data. 10th World Congress on Genetics Applied to Livestock Production (WCGALP), 17 Aug 2014, Vancouver, Canada, Paper, 2014. 3 p.

Vancouver

Brøndum RF, Su G, Janss L, Sahana G, Lund MS. Genomic prediction using QTL derived from whole genome sequence data. 2014. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada.

Author

Brøndum, Rasmus Froberg ; Su, Guosheng ; Janss, Luc ; Sahana, Goutam ; Lund, Mogens Sandø. / Genomic prediction using QTL derived from whole genome sequence data. Paper presented at 10th World Congress on Genetics Applied to Livestock Production (WCGALP), Vancouver, Canada.3 p.

Bibtex

@conference{34a95b06c435429b9002b0563d824b4e,
title = "Genomic prediction using QTL derived from whole genome sequence data",
abstract = "This study investigated the gain in accuracy of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k SNP data. Analyses were performed for Nordic Holstein and Danish Jersey animals, using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model, results showed increases in accuracy of up to two percentage points for production traits in both Holstein and Jersey animals by including the extra variants in the analysis, and an extra 1.5 percentage points for fertility in Jersey animals. When using a Bayesian model accuracies were generally higher, but only small increases in accuracy of up to 0.6 percentage points were observed for the Holstein animals when including the extra markers, while both increases and decreases were observed for Jersey",
keywords = "custom chip, genomic prediction, QTL",
author = "Br{\o}ndum, {Rasmus Froberg} and Guosheng Su and Luc Janss and Goutam Sahana and Lund, {Mogens Sand{\o}}",
year = "2014",
month = "8",
day = "17",
language = "English",
note = "10th World Congress on Genetics Applied to Livestock Production (WCGALP), WCGALP ; Conference date: 17-08-2014 Through 22-08-2014",

}

RIS

TY - CONF

T1 - Genomic prediction using QTL derived from whole genome sequence data

AU - Brøndum, Rasmus Froberg

AU - Su, Guosheng

AU - Janss, Luc

AU - Sahana, Goutam

AU - Lund, Mogens Sandø

PY - 2014/8/17

Y1 - 2014/8/17

N2 - This study investigated the gain in accuracy of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k SNP data. Analyses were performed for Nordic Holstein and Danish Jersey animals, using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model, results showed increases in accuracy of up to two percentage points for production traits in both Holstein and Jersey animals by including the extra variants in the analysis, and an extra 1.5 percentage points for fertility in Jersey animals. When using a Bayesian model accuracies were generally higher, but only small increases in accuracy of up to 0.6 percentage points were observed for the Holstein animals when including the extra markers, while both increases and decreases were observed for Jersey

AB - This study investigated the gain in accuracy of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k SNP data. Analyses were performed for Nordic Holstein and Danish Jersey animals, using either a genomic BLUP or a Bayesian variable selection model. When using the genomic BLUP model, results showed increases in accuracy of up to two percentage points for production traits in both Holstein and Jersey animals by including the extra variants in the analysis, and an extra 1.5 percentage points for fertility in Jersey animals. When using a Bayesian model accuracies were generally higher, but only small increases in accuracy of up to 0.6 percentage points were observed for the Holstein animals when including the extra markers, while both increases and decreases were observed for Jersey

KW - custom chip

KW - genomic prediction

KW - QTL

M3 - Paper

ER -