Genomic regions involved in productivity of two interspecific poplar families in Europe. 2. Biomass production and its relationships with tree architecture and phenology

Short-rotation coppice of hybrid poplar is a promising renewable feedstock for biofuel production. Breeding for high biomass in short-rotation coppice has started only recently. Two hybrid poplar families were grown at two sites in Europe and phenotyped for a variety of biomass-related traits (1) to examine the extent of phenotypic and genetic variation in biomass production, ramification, resprouting, and phenology, (2) to search for genomic regions involved in productivity, and (3) to determine the effect of the environment on the expression of these traits. The performance of both families differed within and among sites. A pronounced heterosis was observed in most cases. Moderate to high heritability values were found. Seventeen quantitative trait loci (QTL) for biomass production, 13 for ramification, ten for resprouting, 21 for bud burst, and ten for bud set were identified. Genetic correlations and QTL colocation showed that high wood production was associated with high allocation of wood into branches and with high production of resprouts after coppicing. Correlations and QTL colocation between biomass production and phenology traits were weak. Our study provides valuable information on genomic regions involved in biomass production, ramification, and phenology and on phenotypic and genetic relationships among these three trait categories.     

Genomic regions involved in productivity of two interspecific poplar families in Europe. 2. Biomass production and its relationships with tree architecture and phenology

Short-rotation coppice of hybrid poplar is a promising renewable feedstock for biofuel production. Breeding for high biomass in short-rotation coppice has started only recently. Two hybrid poplar families were grown at two sites in Europe and phenotyped for a variety of biomass-related traits (1) to examine the extent of phenotypic and genetic variation in biomass production, ramification, resprouting, and phenology, (2) to search for genomic regions involved in productivity, and (3) to determine the effect of the environment on the expression of these traits. The performance of both families differed within and among sites. A pronounced heterosis was observed in most cases. Moderate to high heritability values were found. Seventeen quantitative trait loci (QTL) for biomass production, 13 for ramification, ten for resprouting, 21 for bud burst, and ten for bud set were identified. Genetic correlations and QTL colocation showed that high wood production was associated with high allocation of wood into branches and with high production of resprouts after coppicing. Correlations and QTL colocation between biomass production and phenology traits were weak. Our study provides valuable information on genomic regions involved in biomass production, ramification, and phenology and on phenotypic and genetic relationships among these three trait categories.     

Mapping of one major gene and of QTLs involved in resistance to clubroot in Brassica napus

Clubroot, caused by Plasmodiophora brassicae, is a damaging disease of Brassica napus. Genetic control and mapping of loci involved in high and partial quantitative resistance expressed against two single spore isolates (Pb137–522 and K92–16) were studied in the F₁ and DH progenies of the cross Darmor-bzh (resistant) x Yudal (susceptible). The high level of resistance expressed by Darmor-bzh to isolate Pb137–522 was found to be mainly due to a major gene, which we have named Pb-Bn1, located on linkage group (LG) DY4. Partial quantitative resistance showed by Darmor-bzh to the K92–16 isolate arose from the association of at least two additive QTLs detected on LGs DY4 and DY15; the QTL on DY4, explaining 19% of the variance, was mapped at the same position as the major gene Pb-Bn1. Epistatic interactions between nine regions with or without additive effects were detected. The total phenotypic variation accounted for by additive and epistatic QTLs ranged from 62% to 81% depending on the isolate. For one isolate, the relative effect due to additivity was similar to that due to epistasis. Received: 10 November 1999 / Accepted:18 February 2000     

Combining genotype, environment and attribute variables in regression models for predicting the cell-means of multi-environment cultivar trials

 The main objectives of this study were: (1) to develop models which combine variables of genotype, environment and attribute in regression models (GEAR) for increasing the accuracy of predicted cell-means of the genotype×environment two-way table, and (2) to compare GEAR models with the additive main effects and multiplicative interaction (AMMI) model. GEAR models were developed by regressing the observed values on principal components of genotypes (PCG) and environments (PCE). Genetic and environmental attributes were also added to the GEAR models. GEAR and AMMI models were applied to multi-environment trials of triticale (trial 1), maize (trial 2) and broad beans (trial 3). The random data-splitting and cross-validation procedure was used and the root mean square-predicted difference (RMSPD) was computed to validate each model. GEAR models increased the accuracy of predicted cell-means. Attribute variables, such as soil pH, rainfall, altitude and class of genotype, did not improve the best GEAR model of trial 1, but they increased the predictive value of other models. Two iterations of the computer program further refined the best GEAR model. Based on the RMSPD criterion, GEAR models were as good as, or better than, some AMMI truncated models for predicting cell-means. The approximate accuracy gain factors (GF) of the best GEAR model over the raw data were 2.08, 3.02 and 2.22, for trials 1, 2 and 3, respectively. The GF of the best AMMI model were 1.74, 2.28 and 2.32 for trials 1, 2 and 3, respectively. The analysis of variance of the predicted cell means showed that the genotype×environment interaction (GEI) variance was reduced by about 20% in trial 1 and 81% in trial 2. A bias associated with the predicted cell reduced the GEI variability. Advantages of using GEAR models in muti-environment cultivar trials are that they: (1) increase the precision of cell-mean estimates and (2) reduce the GEI variance and increase trait heritability. Received: 15 August 1997 / Accepted: 28 October 1997     

Detection of quantitative trait loci for heading date based on the doubled haploid progeny of two elite Chinese wheat cultivars

Quantitative trait loci (QTLs) with epistatic and QTL × environment (QE) interaction for heading date were studied using a doubled haploid (DH) population containing 168 progeny lines derived from a cross between two elite Chinese wheat cultivars Huapei 3 × Yumai 57 (Triticum aestivum L.). A genetic map was constructed based on 305 marker loci, consisting of 283 SSR loci and 22 EST-SSR markers, which covered a total length of 2141.7 cM with an average distance of 7.02 cM between adjacent markers in the genome. QTL analyses were performed using a mixed linear model approach. Two main-effect QTLs and two pairs of digenic epistatic effects were detected for heading date on chromosomes 1B, 2B, 5D, 6D, 7A, and 7D at three different environments in 2005 and 2006 cropping seasons. A highly significant QTL with an F-value 148.96, designated as Qhd5D, was observed within the Xbarc320-Xwmc215 interval on chromosome 5DL, accounting for 53.19% of the phenotypic variance and reducing days-to-heading by 2.77 days. The Qhd5D closely links with a PCR marker Xwmc215 with the genetic distance 2.1 cM, which can be used in molecular marker-assisted selection (MAS) in wheat breeding programs. Moreover, the Qhd5D was located on the similar position of well-characterised vernalization sensitivity gene Vrn-D1. We are also spending more efforts to develop near-isogenic lines to finely map the Qhd5D and clone the gene Vrn-D1 through map-based cloning. The Qhd1B with additive effect on heading date has not been reported in previous linkage mapping studies, which might be a photoperiod-sensitive gene homoeologous to the Ppd-H2 gene on chromosome 1B. No main-effect QTLs for heading date were involved in epistatic effects.     

Consistent detection of QTLs for crown rust resistance in Italian ryegrass (<Emphasis Type="Italic">Lolium multiflorum</Emphasis> Lam.) across environments and phenotyping methods

Crown rust, caused by Puccinia coronata f. sp. lolii, is one of the most important diseases of temperate forage grasses, such as ryegrasses (Lolium spp.), affecting yield and nutritional quality. Therefore, resistance to crown rust is a major goal in ryegrass breeding programmes. In a two-way pseudo-testcross population consisting of 306 Lolium multiflorum individuals, multisite field evaluations as well as alternative methods based on artificial inoculation with natural inoculate in controlled environments were used to identify QTLs controlling resistance to crown rust. Disease scores obtained from glasshouse and leaf segment test (LST) evaluations were highly correlated with scores from a multisite field assessment (r = 0.66 and 0.79, P < 0.01, respectively) and thus confirmed suitability of these methods for crown rust investigations. Moreover, QTL mapping based on a linkage map consisting of 368 amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers revealed similar results across different phenotyping methods. Two major QTLs were consistently detected on linkage group (LG) 1 and LG 2, explaining up to 56% of total phenotypic variance (V _p). Nevertheless, differences between position and magnitude of QTLs were observed among individual field locations and suggested the existence of specific local pathogen populations. The present study not only compared QTL results among crown rust evaluation methods and environments, but also identified molecular markers closely linked to previously undescribed QTLs for crown rust resistance in Italian ryegrass with the potential to be applied in marker-assisted forage crop breeding. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.