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Сельскохозяйственная биология, 2012, № 3, с. 47-60.

doi: 10.15389/agrobiology.2012.3.47eng

УДК 633.111.1:631.523.4:575.116:581.1:631.811.1

IDENTIFICATION AND MAPPING OF PHYSIOLOGICAL-AGRONOMIC DETERMINANTS OF SPRING SOFT WHEAT (Triticum aestivum L.) IN DOSE GRADIENT OF NITRIC NUTRITION

Yu.V. Chesnokov¹, E.A. Goncharova¹, N.V. Pochepnya¹, M.N. Sitnikov¹, N.V. Kocherina¹, U. Lohwasser², A. Borner²

In spring soft wheat (Triticum aestivum L.) with the use of ITMI mapping population, which was obtained as result of crossing of spring wheat the Opata 85 variety with W7984 synthetic hexaploid, isolated during hybridization of Triticum tauschii (Coss.) Schmahlh. [syn. Aegilops tauschii Coss., Aegilopssquarrosa auct. non L.] (accession CIGM86.940, DD) and tetraploid wheat the Altar 84 (AABB) on different backgrounds on N (without of nitrogen fertilizer, with half and overall dose of nitrogen fertilizer) the authors identified and located on chromosomes 122 QTL (quantitative trait loci). The part of phenotypic variability was established, which determined by each of revealed QTL. The authors detected the significant correlation between established loci and polymorphism on that or other determinant, which was characterized on basis of threshold value of logarithm of odds of LOD-score. The complex estimation of compared average quantities on nitrogen doses was made by variance analysis with calculation of parameters of determinant variations. The coefficients of correlation permit to determine a character adjoined correlation between determinants and gradient of doses of nitrogen nutrition. The obtained data suggests that the combining of specific QTL, revealed in soils with low content of mineral nitrogen and which became in different ecological conditions, can be used for isolation of variants with stable crop capacity.

Keywords: physiological and agronomic traits, mapping, quantitative trait loci, soft spring wheat, gradient doses of nitrogen nutrition.

 

Intensification of nitrogen nutrition of plants (especially – cereals) is quite important task aimed at raising the productivity of agricultural crops. Improved plants with efficient absorption and assimilation of nitrogen fertilizers have better potential to fair yield of grain with a high-quality protein. Today, creation of such plants is mediated by identification of relevant genes involved in these processes and subsequent introduction of them into recipient forms, or using direct methods such as marker assisted selection (MAS).
NO^3- and NH⁴⁺ use to be a source of nitrogen for plant growth and development. During assimilation these ions share the same metabolic pathways under certain conditions, and they also have a number of similar features: being actively absorbed by root cells at low external concentrations; the presence of two high-affinity transport systems (HATS) for NO^3- and one – for NH⁴⁺ -  established by measuring their inflow; the absorption of both ions is permanently controlled process affecting nitrogen status of a plant. Molecular studies suggest that activity of certain genes encoding NO^3- -transporters is induced by NO^3-, while expression of some other such genes is controlled by repression with glutamine. Along with it, there are some differences in absorption of these ions. Besides, different types of plants have peculiarities in utilization of these sources of nitrogen. In this regard, identification of genetic determinants involved in absorption and assimilation of mineral nitrogen is of particular importance for revealing their physiological mechanisms.
Mapping gene loci for quantitative traits (quantitative trait loci, QTLs) is one of major modern tools in studies of their genetic variability. One of such complex commercially valuable traits is nitrogen use efficiency (NUE). A consistency between QTLs for agronomic features and QTLs for physiological traits associated with NUE allows the development of complex economically valuable traits featured by physiological importance, ecological adaptivity and genetic value. Moreover, if gene mapping reveals QTL location coinciding with that of genes involved in nitrogen assimilation, it suggests so-called candidate genes whose allelic variants are responsible for manifestation of observed variability. In such cases, a detection of new candidate genes is possible as well. In the case of clearly identified candidate genes, a desired allele can be transferred into a recipient genotype (eg, carrier of an undesirable allele) to test it for the expected effect. QTLs for adaptation to environmental and physiological stresses, eg. drought tolerance (1, 2), phosphorus deficit (3) or insufficient nitrogen nutrition (4, 5), have been already mapped in some cereals, but only a few works on identification and mapping QTLs for NUE in wheat are available (6, 7). Though, these reports review mainly the detection of genetic determinants for genotype-environment interactions (8-10) without identification and mapping of genetic determinants of mineral nutrition.
Heterogeneous bioavailability of soil NO^3- and NH⁴⁺  is one of key factors provoking violation of mineral nitrogen nutrition. In addition, seasonal and diurnal dynamics of plant growth and other physiological processes cause gradient requirements for nutrients assimilated from soil. This makes quite important to reveal all peculiarities of nitrogen nutrition in plants of different ecological zones (11). Criteria for early diagnostics of plants’ responsiveness to increasing doses of mineral fertilizers were developed in earlier authors’ studies, along with revealing the yield structure in agricultural crops under extreme environmental conditions including limited soil nutrition (12-15). The obtained data suggest that genotype’s responsiveness to mineral nutrition varies from highly reliable strong to almost unreliable one in various combinations of hydrothermal environmental factors. It was found that optimum doses of mineral fertilizers introduced in soil stimulate the activity of attractive system of plants, while excessive doses – suppress it (13). In the case of increased doses, the enhanced intake of assimilates by developing grains was revealed by calculated parameters of attractivity and micro-distribution of plastic substances in the ear (11, 14). These data show genotypic selectivity of plants in respect to soil nutrition elements, such as the gradient of mineral nitrogen supply (15, 16). Experimental simulation and impact on the system genotype-environment can be used as the effective method for rapid detection of genotypes valuable in terms of selection (11). However, a reliable estimate of all costs on target plant products and recoupment of applied soils fertilizers should consider general physiological and specific genetically determined requirements of plants.
The purpose of this study was identification and mapping of chromosomal loci responsible for the expression of important physiological and agronomic quantitative traits, whose manifestation depends on nitrogen use efficiency under different conditions of mineral soil nitrogen in the North-West region of Russia.
Technique. The object of study was spring soft wheat Triticum aestivum L. The mapped population ITMI was obtained through a cross of spring wheat cv Opata 85 with synthetic hexaploid W7984 selected at hybridization of Triticum tauschii (Coss.) Schmahlh. [Syn. Aegilops tauschii Coss., Aegilops squarrosa auct. non L.] (sample CIGM86.940, DD) and tetraploid wheat Altar 84 (AABB). The interspecific hybridization was conducted by Dr. A. Mujeeb-Kazi (Centro Internacional de Mejoramiento de Maíz y Trigo - CIMMYT, International Centre for Maize and Wheat Improvement, El Batan, Mexico) (8). 150 recombinant inbred lines were obtained through a mono-seeded selection up to F8 or F9 (Cornell University, Ithaca, USA). Seeds (10 pcs.) from 114 randomly selected abovementioned lines were kindly provided by Dr. P. Leroy (Institut National de la Rech-erche Agronomique - INRA, the National Institute of Agronomic Research, Clermont-Ferrand, France). Four lines with least viable seeds were excluded and 110 remaining lines were used in this study. Analysis of traits in plants was performed in experimental fields of VIR Pushkin branch  (Vserossiiskii Institut Rastenievodstva – VIR, N.I. Vavilov All-Russia Research and Development Institute of Plant Industry, St. Petersburg-Pushkin, Russia).
In the experimental field there were arranged three linear ditches with the length of about 120 m, width 100-105 cm and depth 40-45 cm with gaps of 70 cm. From the inside the ditches were laid with plastic film and above it filled with nitrogen-depleted soil (pH = 7,1; contents of phosphorus oxide, potassium oxide and nitric oxide – respectively, 6,5; 8,2 and 1,9 mg/100 g soil). Uniformly developed plants were obtained at watering once every 2-3 days providing 100-150 ml water per 5 kg soil. A source of mineral nitrogen, potassium and phosphorus were, respectively, NH₄NO₃, K₂SO₄ and Ca(H₂PO₄) x H₂O introduced considering a calculated physiological norm for cereals per 1 kg dry soil: N - 0,15; P – 0,10 and K - 0,10 g of the active ingredient (according to Z.I. Zhurbitsky) (17). The experiment was set in three variants: 0N - without the introduction of nitrogen fertilizer, 1/2N and 1N –  respectively, with half and full dose of N fertilizer (1N was equal to the physiological norm of nitrogen; P and K were provided at such quantities in all variants). The fertilizers were applied during tillering using a common practice (17). In all variants there were sown 25 seeds of each line in two replicates and 20 different quantitative traits were investigated throughout the growing season. The analysis of traits was carried out by methods adopted in VIR (18) in three replications.
QTL-analysis was performed in MapMaker/QTL (19). This computer program is based on calculations of Haldane’s map function (20), so the data of gene maps from GrainGenes database (gopher: http://www.greenge-nes.cit.cornell.edu) were used to convert map distances in MapMaker/EXP 3.0 (21). The obtained data on phenotypic analysis were integrated into the base map of population ITMI (22, 23). QTLs’ location was mapped considering only the markers consistent with Kosambi’s mapping function (24). The gene map with localized QTLs was compared with the known map of chromosomes using QGENE computer program (22).
Reliability of correlations between the identified loci and polymorphism of a particular trait was evaluated upon a threshold value of the likelihood ratio of LOD-score (logarithm of odds) (25-27). Each trait was individually assessed by QTL-analysis accounting only the loci with LOD ≥ 3,0 (p < 0,001), 3,0 > LOD ≥ 2,0 (p < 0,01) and 2,0 > LOD ≥ 1,0 (p < 0,05) (21). The nature of correlations between traits and the gradient nitrogen doses was determined by a calculated correlation coefficients rxy. The ratio rxy to its error was a criterion in reliability test (t-Student test) (28). To perform a complex assessment, mean value of each trait was associated with varying doses of nitrogen using the analysis of variance with calculation of performance variation by F-Fisher's exact test and reliability of the results (29). P<0,05 was adopted as acceptable level of statistical reliability including the probability of error of 5%. Results with p <0,01 were regarded as statistically reliable, p <0,005 and p <0,001 – highly reliable. All the data were calculated in the computer program Statistica 6.0.
Results. During the experiment there were performed in total 1800 measurements of 20 quantitative traits. 122 QTLs were identified, including 43 ones with LOD ≥ 3; 65 — LOD ≥ 2 and 14 — LOD ≥ 1 (Table 1 – see descriptions of traits, location of graphic QTL peaks corresponding to a maximum LOD-score for this QTL), and 19 QTLs with LOD > 4. The loci with LOD-score of 1-2, 2-3 and over 3 were respectively determined as minor, strong and basic. LOD-score and the proportion of phenotypic variation (R2,%) provided by the identified QTLs are shown for each trait separately.
Vegetative growth traits. QTL-analysis of traits related to vegetative growth and development revealed the location of most of them on chromosomes 5A and 7B. Two such QTLs were identified on chromosome 5D. It should be noted that QTLs on 5A chromosome were inherited from the maternal form Opata 85, while QTLs for the same traits inherited from the paternal form W7984 were detected on 7B and 5D. All QTLs located on 5A were mapped in one region of the chromosome regardless of nitrogen nutrition; probably, they belong to one chromosomal locus; a similar fact was found in QTLs on 7B. The proportion of phenotypic variation determined by these loci was quite high: from 11,15% (5A) to 31,87% (7B).
Growth and development of plants was accompanied by changes in distribution of genetic determinants responsible for physiological dynamics of these processes. In early ontogeny, the traits were determined by maternal QTLs located on 5A, later the paternal loci on 7B chromosome “woke up”. Such modification of genetic determinants caused consistent changes in the degree of variation of these traits (from early to later ones), and at the phase sprouts-ripening QTLs on 5D chromosome joined in expression along with QTLs on 7B chromosome.
It is known that genetic determinants for flowering and fruiting traits expressed in higher plants at later developmental stages are often linked with M-V genes affecting growth and viability in early ontogeny. Such systems of genes present in homologous chromosomal segments of related species within the genera Gossypium, Lycopersicon, Triticum, Phaseolus, etc. (30). Several genes determining one trait can be linked to form a block, or they can be located in different chromosomes or in different arms, and their activation is controlled by one gene-coordinator (31). That’s why chromosomal loci shouldn’t be seen as only physical linkage of genes, but as a certain degree of their organic order in a group of functionally related genes, i.e. a block co-adapted genes (32). Apparently, QTLs for traits of vegetative growth and development whose manifestation is controlled by the loci mapped on 5A and 7B chromosomes belong to this type of genes.
Morphophysiological traits. QTL for these traits were dispersed over different chromosomes depending on varying conditions of nitrogen nutrition. So, all QTLs for plant height were detected on 4B and 5A chromosomes, and all of them were inherited from the paternal form. However, increasing the doses of mineral nitrogen caused activation of QTLs located on 2A, 3B and 6A chromosomes which joined the abovementioned QTLs on 4B and 5A (QTL on 2A – inherited from maternal form, 3B and 6A – from paternal one). The degree of phenotypic variability for this trait ranged from 10,27 to 19,27%.
Location of QTLs for the length of top (ear-bearing) internode and stem node size wasn’t stable as well, it was influenced by introduced doses of the fertilizer. Several interesting facts were revealed. Firstly, alleles determining the length of top (ear-bearing) internode were found to be of paternal origin, while stem node size – maternal. Secondly, the length of top (ear-bearing) internode in 1N variant was determined by the same loci with plant height in ½N and 1N variants, which shows the presence of genetic relationship between expression of these important physiological and agronomic traits.
Length and width of flag leaf are the traits important for large-scale production of wheat. QTLs for these traits were identified on different chromosomes (most of them –  on 6B and 5B), though exact location of their peaks wasn’t constant as it changed depending on introduced doses of the fertilizer. All the alleles (except the only one on 3B) were introduced by the maternal form, which suggest the possible presence of blocks of co-adapted genes determining these traits.

 

 

Despite low LOD-score in these cases (sometimes a little above 1,60), the proportion of phenotypic variability was almost the same as for QTLs with LOD = 3,14, which allows considering the location of these minor QTLs on chromosomes as quite reliable. Morphological and physiological traits with similar presentation were described in an earlier authors’ work on barley (15).
Distribution of QTLs for wax coating on the outer and inner side of leaves, as well as on stem and ear, wasn’t much diverse. In all variants these traits were determined primarily by major QTLs located in D-genome (except a few single QTLs on 2A, 4A and 4B chromosomes) and inherited from Opata 85. High LOD-score for wax coating trait – from 2,13 to 13,35 – confirms high stability of its manifestation. At the same time, the gradient of nitrogen supply influenced the number of loci encoding local peculiarities of wax coating.
Difficulty of thrashing was described much similar to the previous trait. Known location of these genes in D-genome was confirmed by the authors’ data. Its major QTLs were mapped on 2D chromosome, along with a few loci located on other chromosomes of A, B genomes. Gradient of nitrogen dose caused variation in number of additional QTLs for this trait, whose LOD-score  ranged from 1,83 to 4,42, and the proportion of phenotypic variation - from 17,07 to 29,07%.
Grain yield traits. Ear length trait was developed mainly under the control of major QTLs located on 4A chromosome (location peak 258,1 cM), all of which were inherited from cv Opata 85. One additional QTL for this trait was detected on 5B chromosome. The number of spikelets per spike was similarly determined by major QTLs located on 4B chromosome (location peak 120,7 cM). A number of spikelets per ear was also influenced by one additional QTL on 7A. Redistribution of these loci for both traits occurred only under the change in dose of nitrogen. QTLs for both these traits were inherited from maternal cv Opata 85, and three of them showed LOD-score over 3.
Number of grains per ear and grain weight per ear had almost similar number of identified and mapped QTLs. In the absence of nitrogen they were located on 7A and 2D chromosomes. In ½N  variant QTLs for both traits were detected on 2B, and one additional QTL for number of grains per ear was mapped on 7B. In 1N variant, location of QTLs for both traits changed – they were detected on 4A, 4D and 5A chromosomes.
Weight of 1000 grains also showed unstable location of corresponding QTLs, which though had a certain pattern of changes in the gradient of nitrogen nutrition. Thus, in all three variants there was detected QTL on 7D chromosome. At the same time, in both 0N and ½N variants one additional QTL was identified on 6D, while in 1N – on 6B.  Similarly, another QTL for weight of 1000 grains was detected on 6A chromosome in variants ½N and 1N,  but in 0N its location changed to 5B. Even when location of these loci coincided, their peaks were recorded on different regions of chromosomes. Despite a relatively low LOD-score for this trait (1,49-3,10), the proportion of phenotypic variation provided by the identified QTLs was, respectively, from 14,10 to 20,59%.
Stability of identified QTLs and reliability of their localization. Molecular genetic mapping of QTLs is one of major modern techniques allowing identification and a controlled transfer of chromosomal loci determining manifestation of economically important traits (33, 34). Specific genetic material not peculiar to a certain region can be quite valuable for breeders improving local varieties and breeding lines. The mapped population of spring wheat ITMI was derived from parental forms quite unusual and distinctive to climatic conditions of the Russian Federation (8, 35, 36), and it is of an undoubted breeding value. At the same time, only reproducible results of QTL-analysis can be useful for plant breeders. A number of QTLs described in the authors’ works satisfy it. Furthermore, the data on QTLs activity depending on environmental conditions can be used in precision agriculture providing necessary conditions for growing and best performance of desired traits.
All the identified QTLs can be divided into two groups - dependent and independent on the gradient of nitrogen dozes, i.e., on a target environmental impact.
Earlier, genetic variability for the trait of grain yield at low doses of nitrogen was revealed in experiments of other researchers who showed a significant interaction between genotype and this environmental impact (37). The absorption of nitrogen was shown as a factor providing a large share of diversity in NUE at low nitrogen content and very important for grain yield. Direct selection of wheat was found to be most effective at low doses of nitrogen fertilizer (38). The efficiency of direct selection was also noted in works performed on double haploid lines grown at low doses of nitrogen fertilizer (39) and a gradient availability of soil nitrogen (40).
Applied importance of grain yield-specific QTLs revealed at low levels of nitrogen fertilizer was shown as a promising feature useful for development of new forms stably yielding even at a low content of mineral nitrogen in soil under different environmental conditions (41). At the same time, it should be noted that in these experiments identification and analysis of QTLs was performed in field conditions typical to a certain ecological point (42), or plants were grown in pots in a greenhouse (6), which conditions were quite different from the authors’ experiments. In the latter case (6), statement of the experiment was not clear (eg., the number of plants of one line per replication grown in one vegetation pot).

 

2. Coefficients of correlation between traits and the gradient of nitrogen nutrition  in plants from the mapped population ITMI of soft spring wheat Triticum aestivum L. (St. Petersburg – Pushkin)
Symbolic  notation	Correlation coefficient rxy	t-statistics	p
VST	0,00	0,00	1,000
VSB	0,07	1,17	0,241
VSH	0,04	0,72	0,473
VSF	0,09	1,52	0,128
VSM	0,63	14,11	0,000
PH	-0,03	-0,45	0,649
StLuI	-0,01	-0,03	0,974
StNS	0,15	2,50	0,013
LFL	0,19	3,12	0,002
LFW	0,15	2,40	0,017
SpL	-0,09	-1,19	0,236
NSpt	-0,06	-0,80	0,419
NSeSp	0,12	1,63	0,105
GMSp	0,07	1,00	0,317
TGM	-0,15	-2,09	0,038
LWBi	-0,07	-1,21	0,226
LWBo	-0,05	-0,87	0,386
StWB	0,01	0,19	0,846
SpWB	0,01	0,10	0,916
DifThC	-0,05	-0,64	0,523
Note. Description of traits for symbolic notations – see Table 1.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In this study, identification and mapping of QTLs was carried out using the same set of lines of the mapped population subject to gradient doses of nitrogen in vegetation experiment performed in field conditions. Such combination of field and pot experiments provided the accuracy of pot tests preventing loss and washing off the fertilizers to adjacent soil along with exact monitoring of vegetation and development of experimental plants, while being quite close to real field conditions important for practical breeding. In most cases, changes in contents of available mineral nitrogen contributed to changes in location of the identified QTLs, or activation of additional QTLs affecting a particular trait. This effect is most likely associated with nature of the interaction genotype-environment. For example, location of QTLs for wax coating traits was stable in all variants of this experiment, while QTLs for grain yield traits changed location depending on the dose of fertilizers. This fact displays realization of adaptive potentials of plants under certain environmental conditions (30, 32, 43-45). Possibly, complex impact of environmental factors significantly defines the features of evolutionarily developed co-adapted gene blocks in each plant species, such as wheat, as well as regularities of its genetic co-adaptation system. The same basis is enabled by evolutionary and developmental "memory" of genetic systems F and R specific to each type of plant (30-32, 46, 47).
At the same time, doses of nitrogen fertilizer were reliably and positively correlated with duration of period sprouts-ripening (correlation coefficient 0,63; without the addition of nitrogen this period was shorter than in two other variants), and weakly positive though reliably correlated (rxy = 0,15-0,19) with flag leaf length and width, as well as stem nod size (Table 2). Besides, there was also a weak negative reliable correlation (rxy= – 0,15) between the weight of 1000 grains and nitrogen supply: in ½N and 1N variants the trait value was lower than in 0N variant. These conclusions are reliably confirmed by data shown in Table 3 (especially F-test and its high significance). The analysis of variance revealed that plant height was mainly influenced by the gradient doses of nitrogen, which caused a non-smooth diversity of this trait over the variants (in particular, plants grown with ½N were on average smaller than in two other variants). The length of top (ear-bearing) internode had a similar regularity, which fact indicates interrelations between these traits.

Another interesting finding of this research was relatively low LOD-score for some of identified QTLs (Table 1). In the literature, LOD-score below 3 is often referred to a low reliability level owing to multiple testing in QTL-analysis (21). In fact, LOD-score is the common logarithm for probability that null hypothesis is false (null hypothesis: two classes of recombinant lines carrying paternal (AA) and maternal (aa) alleles have no reliable phenotypic differences). Therefore, LOD=2 means that the hypothesis alternative to the null hypothesis is more probable in 102 times, LOD = 3 – 103 times, etc. (27). Earlier, it was reported about a comparison of c2-test and  1/A = 1/10-LOD-value where A – limit of a function of type I error (25). It was shown (48) that at high LOD-score 1/A is close to a type I error and, on the contrary, at low LOD-score the error is consistently smaller than 1/A, which suggests LOD-score as relatively conservative estimate. In this case the critical LOD-score = 3 corresponds to the maximum value of a type I error (p <0,001). At the same time, in the case of choosing a very high particular (individual) type I error, eg. 5%, high level of linkage can be reliably found at random (27). In this case, the data of various authors (8, 9) suggest that both major and minor QTLs can be located in the same positions in different experiments even in different years of research, therefore, in this study LOD-score below 3 is also considerable.
Thus, the performed study have demonstrated that activity of genetic determinants providing manifestation of physiological, morphological and agronomic quantitative traits depends on doses of introduced mineral nitrogen. The authors have revealed genomic regions involved in control of mineral nitrogen metabolism, including formation of traits related to vegetative growth and grain yield of spring wheat, which data can be used in breeding programs using identification and practical transfer of allelic variants of genetic determinants for physiological and economically important traits.

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1N.I. Vavilov All-Russia Research and Development Institute of Plant Growing, RAAS, St. Petersburg 190000, Russia e-mail: yu.chesnokov@vir.nw.ru; 2Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstr. 3, 06466 Gatersleben, Germany

Received January 11, 2012