Evaluation of the efficiency of genomic versus pedigree predictions for growth and wood quality traits in Scots pine
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F20%3A84470" target="_blank" >RIV/60460709:41210/20:84470 - isvavai.cz</a>
Result on the web
<a href="https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-07188-4" target="_blank" >https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-020-07188-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s12864-020-07188-4" target="_blank" >10.1186/s12864-020-07188-4</a>
Alternative languages
Result language
angličtina
Original language name
Evaluation of the efficiency of genomic versus pedigree predictions for growth and wood quality traits in Scots pine
Original language description
Background. Genomic selection (GS) or genomic prediction is a promising approach for tree breeding to obtain higher genetic gains by shortening time of progeny testing in breeding programs. As proof of concept for Scots pine (Pinus sylvestris L.), a genomic prediction study was conducted with 694 individuals representing 183 full sib families that were genotyped with genotyping by sequencing (GBS) and phenotyped for growth and wood quality traits. 8719 SNPs were used to compare different genomic with pedigree prediction models. Additionally, four prediction efficiency methods were used to evaluate the impact of genomic breeding value estimations by assigning diverse ratios of training and validation sets, as well as several subsets of SNP markers. Results. Genomic Best Linear Unbiased Prediction (GBLUP) and Bayesian Ridge Regression (BRR) combined with expectation maximization (EM) imputation algorithm showed slightly higher prediction efficiencies than Pedigree Best Linear Unbiased Prediction (PBLUP
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
40102 - Forestry
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
BMC GENOMICS
ISSN
1471-2164
e-ISSN
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Volume of the periodical
21
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
17
Pages from-to
0-0
UT code for WoS article
000594316500005
EID of the result in the Scopus database
2-s2.0-85096037889