Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F15%3A67069" target="_blank" >RIV/60460709:41320/15:67069 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1186/s12864-015-1597-y" target="_blank" >http://dx.doi.org/10.1186/s12864-015-1597-y</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s12864-015-1597-y" target="_blank" >10.1186/s12864-015-1597-y</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing

Popis výsledku v původním jazyce

Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits with low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost. Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites. Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about traits architecture. The RR-BLUP GS prediction model produced better accuracies than the GRR supporting traits? complex architecture. GS prediction accuracies for multi-site were high and better than those of single-sites w

Název v anglickém jazyce

Prediction accuracies for growth and wood attributes of interior spruce in space using genotyping-by-sequencing

Popis výsledku anglicky

Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits with low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost. Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites. Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about traits architecture. The RR-BLUP GS prediction model produced better accuracies than the GRR supporting traits? complex architecture. GS prediction accuracies for multi-site were high and better than those of single-sites w

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

GK - Lesnictví

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

BMC GENOMICS

ISSN

1471-2164

e-ISSN

—

Svazek periodika

16

Číslo periodika v rámci svazku

370

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

16

Strana od-do

1-16

Kód UT WoS článku

000354175900004

EID výsledku v databázi Scopus

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