QTL for yield in bioenergy Populus: identifying G×E interactions from growth at three contrasting sites

Abstract

Populus is a genus of fast growing trees that may be suitable as a bioenergy crop grown in short rotation, but understanding the genetic nature of yield and genotype interactions with the environment is critical in developing new high-yield genotypes for wide-scale planting. In the present study, 210 genotypes from an F 2 population (Family 331; POP1) derived from a cross between Populus trichocarpa 93-968 and P. deltoides ILL-129 were grown in southern UK, central France and northern Italy. The performance of POP1, based upon first-and second-year main stem traits and biomass production, improved from northern to southern Europe. Trees at the Italian site produced the highest mean biomass ranging from 0.77 to 18.06 oven-dried tonnes (ODT) ha −1 year −1 , and the UK site produced the lowest mean biomass ranging from 0.18 to 10.31 ODT ha −1 year −1 . Significant genotype×environ-ment interactions were seen despite heritability values across sites being moderate to high. Using a pseudotestcross analysis, 37 quantitative trait loci (QTL) were identified for the maternal parent and 45 for the paternal parent for eight stem and biomass traits across the three sites. High genetic correlations between traits suggested that collocating QTL could be inferred as a single pleiotropic QTL, reducing the number of unique QTL to 23 and 24 for the maternal and paternal parent, respectively. Additive genetic effects were seen to differ significantly for eight QTL on the maternal map and 20 on the paternal map across sites. An additive main effects and multiplicative interaction analysis was carried out to obtain stability parameters for each trait. These parameters were mapped as QTL, and collocation to trait QTL was accessed. Two of the eight stability QTL collocate to trait QTL on the maternal map, and 8 of the 20 stability QTL collocate to trait QTL on the paternal map, suggesting that a regulatory gene model is prevalent over an allele sensitivity model for stem trait stability across these environments.

Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

“…;Chambel et al 2008;Falkenhagen 1996;Kim et al 2008), poplars (Populus spp. ; Rae et al 2008), white spruce (Picea glauca (Moench) Voss; Rweyongeza 2011), birch (Betula spp. ; Zhao et al 2014) and lodgepole pine (Pinus contorta Douglas; Wu and Ying 2001).…”

Identification of QTLs for alpha acid content and yield in hop (Humulus Lupulus L.)

“…Since the weather conditions are more changeable than they were (2003 was extremely bad for hop production in Slovenia because of a very dry and hot season) the importance of including more phenotypic data is more evident than has been revealed in other QTL studies (Fanizza et al 2005;Rae et al 2008). Three QTLs, a1-03, a3-04 and a1-06, were detected in the same region, flanked by AFLP markers E-ACC-M-CAA-103F* and P-ACA-M-CAC-412F on LG03 of the Hallertauer Magnum map.…”

“…Many agriculturally important traits such as quality and quantity of yield, and some forms of disease resistance, are controlled by many genes and are known as quantitative traits. Early stage selection is highly desirable, especially in perennial species, so reports of QTL mapping for studying gene expression at different developmental stages are common (Wu et al 2000;Lercetau et al 2000;Yin et al 2003;Atienza et al 2003;Fanizza et al 2005;Rae et al 2008).…”

A Statistical Model for Testing the Pleiotropic Control of Phenotypic Plasticity for a Count Trait

“…The epistatic hypothesis suggests that specific plasticity genes exist that interact epistatically with the loci for the mean value of the trait to regulate environmental sensitivity (gene regulation; Scheiner and Lyman 1989). These hypotheses have been tested with results from QTL mapping in different species from Arabidopsis (Kliebenstein et al 2002;Ungerer et al 2003) to Populus (Wu 1998;Rae et al 2008), Drosophila (Leips and Mackay 2000;Geiger-Thornsberry and Mackay 2002;Anholt and Mackay 2004), and Caenorhabditis (Gutteling et al 2007). All these studies were based on the phenotypic plasticity of continuously varying traits.…”

“…Statistical models for genetic mapping of continuous traits that are normally distributed have been well developed in the past two decades (Lander and Botstein 1989;Jansen and Stam 1994;Zeng 1994;Kao et al 1999;Wu et al 2007;Rae et al 2008). The idea of mapping continuous traits has been extended to map binary or ordinal traits that vary in a discontinuous manner on the basis of a threshold model by assuming a continuously distributed liability underlying these traits (Visscher et al 1996;Xu and Atchley 1996;Yi and Xu 1999;Li et al 2006).…”