Emmanuel Heumez

Genetic differences for nitrogen uptake and nitrogen utilisation efficiencies in winter wheat

Abstract Due to economic and ecological factors, European agricultural practices are likely to go towards extensive systems with lower inputs of nitrogen (N) fertilisers. The objective of this study was to assess varietal differences for N use at two nitrogen levels. A set of 20 winter wheat (Triticum aestivum L.) genotypes was studied over 2 years in northern France on a deep loam soil without (N0) and with 170 kg ha−1 N fertiliser (N+) as ammonium nitrate. Results were consistent on both years as the genotype×year or genotype×year×N level interactions were not significant. The genotype×N level interaction was highly significant except for total N utilisation efficiency (total above-ground dry weight/total above-ground N) and grain N concentration. The genotype×N level interaction for grain yield was mainly due to three contrasting genotypes: Cappelle, a cultivar from the 1940s, had the same yield at N0 and N+; Arche had a high yield at both N levels; and Recital had a high yield with added N and a very low one without N. The number of kernels/ear explained most of the variations of grain yield at N0 (48%) and N+ (80%), and of the interaction (67%). N uptake efficiency (total above-ground N/soil N supply) accounted for 64% of the variation in N use efficiency (grain yield/soil N supply), while at N0 and at N+ it accounted for only 30%. N utilisation efficiency (grain yield/total above-ground N) was then more important at N+ than at N0. Grain N explained most of total plant N variation at both N levels. The interaction for N use efficiency was best explained by the interaction of N uptake (63%). The applications of these results to a breeding programme to create varieties adapted to low-input management systems are discussed.

Anthesis date mainly explained correlations between post-anthesis leaf senescence, grain yield, and grain protein concentration in a winter wheat population segregating for flowering time QTLs

The genetic variability of the duration of leaf senescence during grain filling has been shown to affect both carbon and nitrogen acquisition. In particular, maintaining green leaves during grain filling possibly leads to increased grain yield, but its associated effect on grain protein concentration has not been studied. The aim of this study was to dissect the genetic factors contributing to correlations observed at the phenotypic level between leaf senescence during grain filling, grain protein concentration, and grain yield in winter wheat. With this aim in view, an analysis of quantitative trait locus (QTL) co-locations for these traits was carried out on a doubled haploid mapping population grown in a large multienvironment trial network. Pleiotropic QTLs affecting leaf senescence and grain yield and/or grain protein concentration were identified on chromosomes 2D, 2A, and 7D. These were associated with QTLs for anthesis date, showing that the phenotypic correlations with leaf senescence were mainly explained by flowering time in this wheat population. Study of the allelic effects of these pleiotropic QTLs showed that delaying leaf senescence was associated with increased grain yield or grain protein concentration depending on the environments considered. It is proposed that this differential effect of delaying leaf senescence on grain yield and grain protein concentration might be related to the nitrogen availability during the post-anthesis period. It is concluded that the benefit of using leaf senescence as a selection criterion to improve grain protein concentration in wheat cultivars may be limited and would largely depend on the targeted environments, particularly on their nitrogen availability during the post-anthesis period.

Deviation from the grain protein concentration–grain yield negative relationship is highly correlated to post-anthesis N uptake in winter wheat

In plants, carbon and nitrogen (N) economies are intimately linked at the physiological and biochemical level. The strong genetic negative correlation between grain yield and grain protein concentration observed in various cereals is an illustration of this inter-relationship. Studies have shown that deviation from this negative relationship (grain protein deviation or GPD) has a genetic basis, but its physiological basis is still poorly understood. This study analysed data on 27 genotypes grown in multienvironment field trials, representing a wide range of agricultural practices and climatic conditions. The objective was to identify physiological processes related to the genetic variability in GPD. Under most environments, GPD was significantly related to post-anthesis N uptake independently of anthesis date and total N at anthesis. The underlying physiological trait might be related to genotypic differences in either access to soil N, regulation of N uptake by plant N status, or ability to maintain root activity during the grain-filling period. GPD is an interesting potential target in breeding as it appears to be relatively robust across different environments and would be valuable in increasing total N uptake by maturity.

Detection and mapping of QTL for earliness components in a bread wheat recombinant inbred lines population

Earliness, an adaptative trait and factor of variation for agronomic characters, is a major trait in plant breeding. Its constituent traits, photoperiod sensitivity (PS), vernalization requirement (VR) and intrinsic earliness (IE), are largely under independent genetic controls. Mapping of major genes and quantitative trait loci (QTL) controlling these components is in progress. Most of the studies focusing on earliness considered it as a whole or through one (or two) of its components. The purpose of this study was to detect and map QTL for the three traits together through an experimental design combining field trials and controlled growth conditions. QTL were mapped in a population of F7 recombinant inbred lines derived by single-seed descent from a cross between two French varieties, ‘Renan’ and ‘Récital’. A map was previously constructed, based on 194 lines and 254 markers, covering about 77% of the genome. Globally, 13 QTL with a LOD>2.5 were detected, of which four control PS, five control VR and four control IE. Two major photoperiod sensitive QTL, together explaining more than 31% of the phenotypic variation, were mapped on chromosomes 2B and 2D, at the same position as the two major genes Ppd-B1 and Ppd-D1. One major VR QTL explaining (depending on the year) 21.8–39.6% of the phenotypic variation was mapped on 5A. Among the other QTL, two QTL of PS and VR not referenced so far were detected on 5A and 6D, respectively. A VR QTL already detected on 2B in a connected population was confirmed.

Genome-wide association mapping of three important traits using bread wheat elite breeding populations

The exponential development of molecular markers enables a more effective study of the genetic architecture of traits of economic importance, like test weight in wheat (Triticum aestivum L.), for which a high value is desired by most end-users. The association mapping (AM) method now allows more precise exploration of the entire genome. AM requires populations with substantial genetic variability of the traits of interest. The breeding lines at the end of a selection cycle, characterized for numerous traits, represent a potentially useful population for AM studies. Using three elite line populations, selected by several breeders and genotyped with about 2,500 Diversity Arrays Technology markers, several associations were identified between these markers and test weight, grain yield and heading date. To minimize spurious associations, we compared the general linear model and mixed linear model (MLM), which adjust for population structure and kinship differently. The MLM model with the kinship matrix was the most efficient. Finally, elite lines from several breeding programs had sufficient genetic variability to allow for the mapping of several chromosomal regions involved in the variation of three important traits.

Identifying wheat genomic regions for improving grain protein concentration independently of grain yield using multiple inter-related populations

Grain yield (GY) and grain protein concentration (GPC) are two major traits contributing to the economic value of the wheat crop. These are, consequently, major targets in wheat breeding programs, but their simultaneous improvement is hampered by the negative correlation between GPC and GY. Identifying the genetic determinants of GPC and GY through quantitative trait loci (QTL) analysis would be one way to identify chromosomal regions, allowing improvement of GPC without reducing GY using marker-assisted selection. Therefore, QTL detection was carried out for GY and GPC using three inter-connected doubled haploid populations grown in a large multi-environment trial network. Chromosomes 2A, 2D, 3B, 7B and 7D showed co-location of QTL for GPC and GY with antagonistic effects, thus contributing to the negative GPC–GY relationship. Nonetheless, genomic regions determining GPC independently of GY across experiments were found on chromosomes 3A and 5D and could help breeders to move the GPC–GY relationship in a desirable direction.

Bread wheat milling behavior: effects of genetic and environmental factors, and modeling using grain mechanical resistance traits

Key messageGenetic (Pinb-D1 alleles) and environment (through vitreousness) have important effects on bread wheat milling behavior. SKCS optimal values corresponding to soft vitreous or hard mealy grains were defined to obtain the highest total flour yield.AbstractNear-isogenic lines of bread wheat that differ in hardness, due to distinct puroindoline-b alleles (the wild type, Pinb-D1a, or the mutated forms, Pinb-D1b or Pinb-D1d), were grown in different environments and under two nitrogen fertilization levels, to study genetic and environmental effects on milling behavior. Milling tests used a prototype mill, equipped with two break steps, one sizing step, and two reduction steps, and this enabled 21 individual or aggregated milling fractions to be collected. Four current grain characters, thousand grain weight, test weight, grain diameter, and protein content, were measured, and three characters known to influence grain mechanical resistance, NIRS hardness, SKCS hardness index, and grain vitreousness (a character affecting the grain mechanical behavior but generally not studied). As expected, the wild type or mutated forms of Pinb-D1 alleles led to contrasted milling behavior: soft genotypes produced high quantities of break flour and low quantities of reduction flour, whereas reverse quantities were observed for hard genotypes. This different milling behavior had only a moderate influence on total flour production. NIRS hardness and vitreousness were, respectively, the most important and the second most important grain characters to explain milling behavior. However, contrary to NIRS hardness, vitreousness was only involved in endosperm reduction and not in the separation between the starchy endosperm and the outer layers. The highest flour yields were obtained for SKCS values comprised between 30 and 50, which corresponded either to soft vitreous or hard mealy grains. Prediction equations were defined and showed a good accuracy estimating break and reduction flours portions, but should be used more cautiously for total flour.