Complex Agronomic Traits Research Articles

Potential of genomic selection in rapeseed (Brassica napus L.) breeding

AbstractGenomic selection employs genome‐wide marker data to predict genomic breeding values. In this study, a population consisting of 391 lines of elite winter oilseed rape derived from nine families was used to evaluate the prospects of genomic selection in rapeseed breeding. All lines have been phenotyped for six morphological, quality‐ and yield‐related traits and genotyped with genome‐wide SNP markers. We used ridge regression best linear unbiased prediction in combination with cross‐validation and obtained medium to high prediction accuracies for the studied traits. Our results illustrate that among‐family variance contributes to the prediction accuracy and can lead to an overestimation of the prospects of genomic selection within single segregating families. We also tested a scenario where estimation of effects was carried out without individuals from the family in which breeding values were predicted, which yielded lower but nevertheless attractive prediction accuracies. Taken together, our results suggest that genomic selection can be a valuable genomic approach for complex agronomic traits towards a knowledge‐based breeding in rapeseed.

Gene SGL, encoding a kinesin-like protein with transactivation activity, is involved in grain length and plant height in rice

Grain shape, a complex agronomic trait, plays an important role in determining yield and quality in rice. In the present study, a mutant named short grain length (sgl) was identified among explants of tissue cultured japonica variety Kita-ake. It exhibited reduced plant height (about 72 % of WT) and short grain length (about 80 % of WT). The reduced length was due to decreased cell elongation. The Short Grain Length (SGL) gene was isolated via map-based cloning and identified to encode a kinesin-like protein. SGL was expressed in the whole plant, especially in the stem and panicles. SGL was shown to have transcriptional activity. In onion epidermal cells, SGL protein was found mainly in the nucleus. Real-time PCR analyses showed that expression levels of genes involved in gibberellin metabolic pathways were affected in the sgl mutant. These data suggested that SGL protein may be involved in regulating GA synthesis and response genes, that in turn, regulates grain length and plant height.

Association mapping of six yield-related traits in rapeseed (Brassica napus L.)

Yield is one of the most important traits for rapeseed (Brassica napus L.) breeding, but its genetic basis remains largely ambiguous. Association mapping has provided a robust approach to understand the genetic basis of complex agronomic traits in crops. In this study, a panel of 192 inbred lines of B. napus from all over the world was genotyped using 451 single-locus microsatellite markers and 740 amplified fragment length polymorphism markers. Six yield-related traits of these inbred lines were investigated in three consecutive years with three replications, and genome-wide association studies were conducted for these six traits. Using the model controlling both population structure and relative kinship (Q + K), a total of 43 associations (P < 0.001) were detected using the means of the six yield-related traits across 3 years, with two to fourteen markers associated with individual traits. Among these, 18 markers were repeatedly detected in at least 2 years, and 12 markers were located within or close to QTLs identified in previous studies. Six markers commonly associated with correlated traits. Conditional association analysis indicated that five of the associations between markers and correlated traits are caused by one QTL with pleiotropic effects, and the remaining association is caused by linked but independent QTLs. The combination of favorable alleles of multiple associated markers significantly enhances trait performance, illustrating a great potential of utilization of the associations in rapeseed breeding programs.

Validation of a functional molecular marker suitable for marker-assisted breeding for fruit texture in apple (Malus × domestica Borkh.)

Molecular markers are nowadays considered fundamental tools in breeding programs, supporting the selection of the most favourable offspring. This role is invaluable in the case of complex agronomic traits in tree fruit crop species, such as fruit texture in apple (Malus × domestica Borkh.). This work presents the validation of a previously identified functional simple sequence repeat marker, named Md-PG1SSR10kd, suitable for the advanced selection of high texture performance seedlings. Two independent populations were chosen by marker-assisted parent selection, and a specific set of seedlings was selected by marker-assisted seedling selection, to validate the predictive power of this marker. The two groups of seedlings, further phenotyped for fruit texture, showed a clear difference in texture behaviour. The selection of this marker also showed a higher efficiency than Md-ACS1 and Md-ACO1, two functional markers currently implemented in different breeding programs. Finally, the allelic effect was estimated by computing the breeding values in a collection of 83 different apple cultivars. The results reported here confirmed the association of Md-PG1SSR10kd with texture sub-traits, proposing this as a novel promising selection strategy suitable for apple fruit texture.

RiceFREND: a platform for retrieving coexpressed gene networks in rice

Similarity of gene expression across a wide range of biological conditions can be efficiently used in characterization of gene function. We have constructed a rice gene coexpression database, RiceFREND (http://ricefrend.dna.affrc.go.jp/), to identify gene modules with similar expression profiles and provide a platform for more accurate prediction of gene functions. Coexpression analysis of 27 201 genes was performed against 815 microarray data derived from expression profiling of various organs and tissues at different developmental stages, mature organs throughout the growth from transplanting until harvesting in the field and plant hormone treatment conditions, using a single microarray platform. The database is provided with two search options, namely, ‘single guide gene search’ and ‘multiple guide gene search’ to efficiently retrieve information on coexpressed genes. A user-friendly web interface facilitates visualization and interpretation of gene coexpression networks in HyperTree, Cytoscape Web and Graphviz formats. In addition, analysis tools for identification of enriched Gene Ontology terms and cis-elements provide clue for better prediction of biological functions associated with the coexpressed genes. These features allow users to clarify gene functions and gene regulatory networks that could lead to a more thorough understanding of many complex agronomic traits.

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize

The diversity of metabolites found in plants is by far greater than in most other organisms. Metabolic profiling techniques, which measure many of these compounds simultaneously, enabled investigating the regulation of metabolic networks and proved to be useful for predicting important agronomic traits. However, little is known about the genetic basis of metabolites in crops such as maize. Here, a set of 289 diverse maize inbred lines was genotyped with 56,110 SNPs and assayed for 118 biochemical compounds in the leaves of young plants, as well as for agronomic traits of mature plants in field trials. Metabolite concentrations had on average a repeatability of 0.73 and showed a correlation pattern that largely reflected their functional grouping. Genome-wide association mapping with correction for population structure and cryptic relatedness identified for 26 distinct metabolites strong associations with SNPs, explaining up to 32.0% of the observed genetic variance. On nine chromosomes, we detected 15 distinct SNP-metabolite associations, each of which explained more then 15% of the genetic variance. For lignin precursors, including p-coumaric acid and caffeic acid, we found strong associations (P values to ) with a region on chromosome 9 harboring cinnamoyl-CoA reductase, a key enzyme in monolignol synthesis and a target for improving the quality of lignocellulosic biomass by genetic engineering approaches. Moreover, lignin precursors correlated significantly with lignin content, plant height, and dry matter yield, suggesting that metabolites represent promising connecting links for narrowing the genotype-phenotype gap of complex agronomic traits.

Ploidy and Hybridity Effects on Growth Vigor and Gene Expression inArabidopsis thalianaHybrids and Their Parents

Both ploidy and hybridity affect cell size and growth vigor in plants and animals, but the relative effects of genome dosage and hybridization on biomass, fitness, and gene expression changes have not been systematically examined. Here we performed the first comparative analysis of seed, cell, and flower sizes, starch and chlorophyll content, biomass, and gene expression changes in diploid, triploid, and tetraploid hybrids and their respective parents in three Arabidopsis thaliana ecotypes: Columbia, C24, and Landsberg erecta (Ler). Ploidy affects many morphological and fitness traits, including stomatal size, flower size, and seed weight, whereas hybridization between the ecotypes leads to altered expression of central circadian clock genes and increased starch and chlorophyll content, biomass, and seed weight. However, varying ploidy levels has subtle effects on biomass, circadian clock gene expression, and chlorophyll and starch content. Interestingly, biomass, starch content, and seed weight are significantly different between the reciprocal hybrids at all ploidy levels tested, with the lowest and highest levels found in the reciprocal triploid hybrids, suggesting parent-of-origin effects on biomass, starch content, and seed weight. These findings provide new insights into molecular events of polyploidy and heterosis, as well as complex agronomic traits that are important to biomass and seed production in hybrid and polyploid crops.

Genetic structure and linkage disequilibrium pattern of a rapeseed (Brassica napus L.) association mapping panel revealed by microsatellites

Understanding the population structure and linkage disequilibrium (LD) is a prerequisite for association mapping of complex traits in a target population. In this study, we assessed the genetic diversity, population structure and the extent of LD in a panel of 192 inbred lines of Brassica napus from all over the world using 451 single-locus microsatellite markers. The inbred lines could be divided into P1 and P2 groups by a model-based population structure analysis. Out of the 142 inbred lines in the P1 group, 126 lines were from China and Japan, and the remaining 16 lines were from Europe, Canada and Australia. In the P2 group, 33 out of the 50 lines were from Europe, Canada, and Australia, and the remaining 17 lines were from China. Structure analysis further divided each group into two subgroups. AMOVA, pairwise F (ST) and neutrality analyses confirmed the differentiation between groups and subgroups. More than 80 % of the pairwise kinship estimates between inbred lines were <0.05, indicating that relative kinship is weak in our panel. Only 6 % linked marker pairs showed LD, suggesting the low level of LD in this association panel. The LD decayed within 0.5-1 cM at the genome level, and varied considerably across each group and subgroup, due to the population size, genetic background and genetic drift. The characterization of the population structure and LD patterns would be useful for performing association studies for complex agronomic traits in rapeseed.

Genome-wide association studies for agronomical traits in a world wide spring barley collection

BackgroundGenome-wide association studies (GWAS) based on linkage disequilibrium (LD) provide a promising tool for the detection and fine mapping of quantitative trait loci (QTL) underlying complex agronomic traits. In this study we explored the genetic basis of variation for the traits heading date, plant height, thousand grain weight, starch content and crude protein content in a diverse collection of 224 spring barleys of worldwide origin. The whole panel was genotyped with a customized oligonucleotide pool assay containing 1536 SNPs using Illumina's GoldenGate technology resulting in 957 successful SNPs covering all chromosomes. The morphological trait "row type" (two-rowed spike vs. six-rowed spike) was used to confirm the high level of selectivity and sensitivity of the approach. This study describes the detection of QTL for the above mentioned agronomic traits by GWAS.ResultsPopulation structure in the panel was investigated by various methods and six subgroups that are mainly based on their spike morphology and region of origin. We explored the patterns of linkage disequilibrium (LD) among the whole panel for all seven barley chromosomes. Average LD was observed to decay below a critical level (r2-value 0.2) within a map distance of 5-10 cM. Phenotypic variation within the panel was reasonably large for all the traits. The heritabilities calculated for each trait over multi-environment experiments ranged between 0.90-0.95. Different statistical models were tested to control spurious LD caused by population structure and to calculate the P-value of marker-trait associations. Using a mixed linear model with kinship for controlling spurious LD effects, we found a total of 171 significant marker trait associations, which delineate into 107 QTL regions. Across all traits these can be grouped into 57 novel QTL and 50 QTL that are congruent with previously mapped QTL positions.ConclusionsOur results demonstrate that the described diverse barley panel can be efficiently used for GWAS of various quantitative traits, provided that population structure is appropriately taken into account. The observed significant marker trait associations provide a refined insight into the genetic architecture of important agronomic traits in barley. However, individual QTL account only for a small portion of phenotypic variation, which may be due to insufficient marker coverage and/or the elimination of rare alleles prior to analysis. The fact that the combined SNP effects fall short of explaining the complete phenotypic variance may support the hypothesis that the expression of a quantitative trait is caused by a large number of very small effects that escape detection. Notwithstanding these limitations, the integration of GWAS with biparental linkage mapping and an ever increasing body of genomic sequence information will facilitate the systematic isolation of agronomically important genes and subsequent analysis of their allelic diversity.

Genetic architecture of complex agronomic traits examined in two testcross populations of rye (Secale cereale L.)

BackgroundRye is an important European crop used for food, feed, and bioenergy. Several quality and yield-related traits are of agronomic relevance for rye breeding programs. Profound knowledge of the genetic architecture of these traits is needed to successfully implement marker-assisted selection programs. Nevertheless, little is known on quantitative loci underlying important agronomic traits in rye.ResultsWe used 440 F3:4 inbred lines from two biparental populations (Pop-A, Pop-B) fingerprinted with about 800 to 900 SNP, SSR and/or DArT markers and outcrossed them to a tester for phenotyping. The resulting hybrids and their parents were evaluated for grain yield, single-ear weight, test weight, plant height, thousand-kernel weight, falling number, protein, starch, soluble and total pentosan contents in up to ten environments in Central Europe. The quality of the phenotypic data was high reflected by moderate to high heritability estimates. QTL analyses revealed a total of 31 QTL for Pop-A and 52 for Pop-B. QTL x environment interactions were significant (P < 0.01) in most cases but variance of QTL main effect was more prominent.ConclusionsQTL mapping was successfully applied based on two segregating rye populations. QTL underlying grain yield and several quality traits had small effects. In contrast, thousand-kernel weight, test weight, falling number and starch content were affected by several major QTL with a high frequency of occurrence in cross validation. These QTL explaining a large proportion of the genotypic variance can be exploited in marker-assisted selection programs and are candidates for further genetic dissection.

Association Mapping for Enhancing Maize (Zea mays L.) Genetic Improvement

ABSTRACTAssociation mapping through linkage disequilibrium (LD) analysis is a powerful tool for the dissection of complex agronomic traits and for the identification of alleles that can contribute to the enhancement of a target trait. With the developments of high throughput genotyping techniques and advanced statistical approaches as well as the assembling and characterization of multiple association mapping panels, maize has become the model crop for association analysis. In this paper, we summarize progress in maize association mapping and the impacts of genetic diversity, rate of LD decay, population size, and population structure. We also review the use of candidate genes and gene‐based markers in maize association mapping studies that has generated particularly promising results. In addition, we examine recent developments in genome‐wide genotyping techniques that promise to improve the power of association mapping and significantly refine our understanding of the genetic architecture of complex quantitative traits. The new challenges and opportunities associated with genome‐wide analysis studies are discussed. In conclusion, we review the current and future impacts of association mapping on maize improvement along with the potential benefits for poor people in developing countries who are dependent on this crop for their food security and livelihoods.

Integration of Genomics into Rice Breeding

Abstract One of the major challenges in genetics has been to identify the nucleotide polymorphisms responsible for phenotypic variation. Through intensive analysis, several major quantitative trait loci (QTLs) for agronomic traits in rice have been identified and the underlying candidate genes have been delimited. Advanced mapping populations, including chromosome segment substitution lines, have enhanced the power of genetic analysis to detect QTL alleles, even those with minor effects. Recent examples of marker-assisted selection have proven the potential of this strategy for crop improvement. The genome-wide discovery of single nucleotide polymorphisms (SNPs), even among closely related cultivars, has enhanced the power of allele mining in a wide range of rice breeding materials. An array-based SNP genotyping system can be used to visualize pedigree haplotypes in breeding materials, including landraces and modern cultivars. All of these technologies are accelerating the genetic dissection of complex agronomic traits and further improvement of rice.

Expression QTLs: applications for crop improvement

In the past, plant breeders dealt with complex agronomic traits in crops, such as drought, pest resistance, yield, and standability, through field observations and standard breeding practices. The evolution to molecular breeding has yielded a deeper understanding of the interacting quantitative trait loci (QTLs) of the complex traits and has exposed underlying genetic variation useful in marker-assisted breeding. Current momentum in QTL analysis is toward understanding the genetic regulation of gene expression as studied by the quantification of transcript levels of genes, or expression QTL (eQTL). Large scale microarray studies have elucidated the genetic regulation of entire transcriptomes, in the process known as genetical genomics, and are beginning to build biochemical pathways of interacting genes on the basis of variations in transcript levels. In addition to understanding general patterns of gene expression, these genetical genomic studies are creating caches of information useful for a multitude of applications. As one gene regulates the level of expression of another (trans-acting eQTL), novel upstream or downstream components in gene regulation pathways can be identified. In addition to steady state analysis, the induction of stimuli such as drought can lead to a deeper understanding of gene networks that are activated under such conditions. Correlation of measured transcript levels (eQTL phenotype) with classic QTL phenotypes may suggest functional roles for the allelic variation in gene expression and serve as a predictor of downstream effects on plant development, morphology, and agronomic interest. Finally, the analysis of the activation of particular genes under steady state or external stimuli treatment provides insight into the functionality of endogenous promoters. While promoters used for transgenic expression have been thoroughly analyzed in model systems and model inbred lines, the understanding of agronomically important phenotypes may benefit from the analysis of genetic polymorphisms of trans-acting regulators affecting transgene expression, and therefore can allow for the optimization of expression both of current and future transgenic lines.

Principles and practices of plant genomics. Volume 2: Molecular breeding

Principles and practices of plant genomics. Volume 2: Molecular breeding

QTLs in rice breeding: examples for abiotic stresses

Despite the status of rice as a model agricultural crop and hundreds of studies identifying quantitative trait loci (QTLs), the applications of these results in breeding have been limited. However, the success of plant breeders in developing varieties with high yield, excellent grain quality, and wide adaptation that are widely grown by farmers (i.e., mega varieties) has provided an opportunity to deploy the most useful QTLs for rice improvement. Marker-assisted backcrossing (MAB) facilitates the precise introgression of a desired trait into the original genetic background of such mega varieties. QTLs with a large effect are rare for complex agronomic traits like yield, but are more common for other traits such as resistance to abiotic stresses. Here we discuss the example of submergence tolerance. Much of the tolerance in varieties such as FR13A has been shown to be under the control of the Sub1 locus, which includes 2–3 tightly-linked putative transcription factors. Sub1 was transferred into the Indian cultivar Swarna, resulting in a new version of this mega variety with tolerance of submergence. Large QTLs also exist for tolerance of salinity, P deficiency, Al toxicity, and low temperature. With some modifications, this approach may be applicable for traits controlled by multiple smaller QTLs. However, strategies for transferring multiple QTLs into mega varieties need to be developed such that negative effects of the transferred segments (linkage drag) do not adversely affect the resulting varieties. Furthermore, strategies for reducing the costs associated with marker genotyping and efficient phenotyping also need to be developed and adopted in order to apply MAB on a larger scale.

Mapping quantitative trait loci for growth responses to exogenously applied stress induced hormones in wheat

Biotic and abiotic stresses are responsible for much of the variation in wheat production worldwide. The plant, in responding to stress events, increases the endogenous synthesis of hormones such as Abscisic Acid, Ethylene, Jasmonic Acid and Salicylic Acid. This paper was aimed at determining the location of plant-defence genes triggered by treatment with stress-induced hormones in a set of recombinant doubled haploid substitution lines involving variation for a single chromosome, 6A, previously shown to carry genes for aphid resistance. Eighty-three doubled haploid recombinant substitution (DHR) lines for chromosome 6A derived from the F1 of “Chinese Spring” (CS) × “Chinese Spring (Synthetic 6A)” (S6A) substitution line, were used as a mapping population. Plants of every genotype at the fully expanded 3rd leaf stage were subjected to four hormone treatments: ethylene (E), jasmonic acid (J), salicylic acid (S) and abscisic acid (A), together with an untreated control. The changes in a range of phenotypic traits were measured, aerial fresh weight (AFWC), aerial dry weight (ADWC), root fresh weight (RFWC), root dry weight (RDWC), foliar area (FAC). These were recorded twice: at the onset of the experiment before spraying with hormones and 72 h later. Nine QTLs were detected which were significantly associated with 6A molecular markers, explaining the variation for ADWC, RDWC and FAC. Most of the QTLs were associated with the interval between loci Xgwm459 and Xgwm334a, located in the telomeric region of the short arm of 6A. The dissection of complex agronomic traits such as tolerance to stress and QTLs related to exogenous hormone treatments could be used in marker-assisted selection for breeding wheat with tolerance to stresses.

A comparison of strategies for transformation with multiple genes via microprojectile-mediated bombardment

The stable insertion and expression of multiple transgenes in crops is highly desirable, as the manipulation of complex agronomic traits and the introduction of novel biosynthetic pathways are dependent upon it. This study was performed to explore the frequency and efficiency of introducing multiple genes in soybean by using somatic embryogenesis and microprojectile bombardment transformation. The co-transformation frequency of six selectable marker or reporter genes (GusA, bleomycin resistance, glufosinate resistance, hygromycin resistance, green fluorescent protein, and kanamycin resistance) were followed throughout the T0, T1, and T2 generations. Three bombardment strategies were compared to determine the best method to generate transgenic plants that express the introduced transgenes and have a simple insertion pattern that would facilitate any downstream breeding. The plasmid bombardment treatments were (1) a six-gene-containing plasmid, (2) an equimolar treatment of five individual plasmids that collectively contained the six transgenes of interest (genes of glufosinate and hygromycin resistance were on the same plasmid), and (3) a 1:9 ratio mixture of the five plasmids, in which the plasmid containing the selectable marker used in the regeneration process, hygromycin resistance, was used in ninefold excess to all the other plasmids. Of the six bombardments performed per plasmid treatment, the results of seven independent events for the six-gene plasmid, four events for the 1:9 treatment, and a single regenerated event for the equimolar treatment indicate that containing all the transgenes on one plasmid just had an advantage in terms of frequency of a successful transformation events. Based on Southern analysis, the only events that contained all six transgenes was the one obtained by the equimolar treatment. No event was obtained that expressed all six transgenes, and certain transgenes seem to be non-randomly lost, namely gusA, bleomycin resistance, and glufosinate resistance, regardless of treatment. The addition of elements to optimize the expression of each gene cassette when multiple genes are in close proximity needs to be further investigated.

Candidate Gene Approach to Identify Genes Underlying Quantitative Traits and Develop Diagnostic Markers in Potato

ABSTRACTPotatoes (Solanum tuberosum L.) and humans (Homo sapiens L.) are both outcrossing species. The phenotypic variation of both is controlled by environmental factors and by natural DNA polymorphisms between individuals. Therefore we adopt similar approaches as used in human population genetics, such as association mapping, to identify loci and their alleles that are causal for complex agronomic characters such as quantitative resistance to pathogens or tuber sugar content. Functional analysis of genes operating in resistance to pests and pathogens or in carbohydrate metabolism, either in potato itself or in other plants including the model species Arabidopsis thaliana (L.) Heynh., provides many functional candidates for these complex agronomic traits. In our approach, functional candidate genes are tested for linkage to quantitative trait loci (QTL) for pathogen resistance or tuber quality traits, thereby selecting positional candidates (genes colocalizing with a QTL). DNA polymorphisms in or physically linked to positional candidate genes are then evaluated in populations of tetraploid potato genotypes and tested for association with phenotypes evaluated in the same populations. We have used the candidate gene approach to identify DNA‐based markers that are diagnostic for quantitative resistance to late blight caused by Phytophthora infestans (Mont.) de Bary, to the root cyst nematode Globodera pallida (Stone), and for chip color in tetraploid potato cultivars and in advanced breeding clones.

Quantitative trait locus analysis as a gene discovery tool.

Quantitative trait locus analysis has been a mainstay approach for obtaining a genetic description of complex agronomic traits for plants. What is sometimes overlooked is the role quantitative trait locus (QTL) analysis can play in identifying genes that underlay complex traits. In this chapter, I will describe the basic steps required to conduct QTL analysis in crop plants. This process involves choices by the investigator on type of population to be studied, molecular marker system to be used to genotype the population, and methods for QTL analysis. Examples of cloned genes, first identified as QTL, are also given to persuade the reader of the power of QTL analysis to discover genes controlling traits and phenotypes.

Genetic manipulation and quantitative-trait loci mapping for nitrogen recycling in rice.

Immunocytological studies in this laboratory have suggested that NADH-dependent glutamate synthase (NADH-GOGAT; EC 1.4.1.14) in developing organs of rice (Oryza sativa L. cv. Sasanishiki) is involved in the utilization of glutamine remobilized from senescing organs through the phloem. Because most of the indica cultivars contained less NADH-GOGAT in their sink organs than japonica cultivars, over-expression of NADH-GOGAT gene from japonica rice was investigated using Kasalath, an indica cultivar. Several T0 transgenic Kasalath lines over-producing NADH-GOGAT under the control of a NADH-GOGAT promoter of Sasanishiki, a japonica rice, showed an increase in grain weight (80% as a maximum), indicating that NADH-GOGAT is indeed a key step for nitrogen utilization and grain filling in rice. A genetic approach using 98 backcross-inbred lines (BC(1)F(6)) developed between Nipponbare (a japonica rice) and Kasalath were employed to detect putative quantitative trait loci (QTLs) associated with the contents of cytosolic glutamine synthetase (GS1; EC 6.3.1.2), which is probably involved in the export of nitrogen from senescing organs and those of NADH-GOGAT. Immunoblotting analyses showed transgressive segregations toward lower or greater contents of these enzyme proteins in these BC(1)F(6). Seven chromosomal QTL regions were detected for GS1 protein content and six for NADH-GOGAT. Some of these QTLs were located in QTL regions for various biochemical and agronomic traits affected by nitrogen recycling. The relationships between the genetic variability of complex agronomic traits and traits for these two enzymes are discussed.