Genomic regions involved in response to grain yield selection at high and low nitrogen fertilization in maize

Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) Under optimum and low nitrogen conditions

Low soil nitrogen levels, compounded by the high costs associated with nitrogen supplementation through fertilizers, significantly contribute to food insecurity, malnutrition, and rural poverty in maize-dependent smallholder communities of sub-Saharan Africa (SSA). The discovery of genomic regions associated with low nitrogen tolerance in maize can enhance selection efficiency and facilitate the development of improved varieties. To elucidate the genetic architecture of grain yield (GY) and its associated traits (anthesis-silking interval (ASI), anthesis date (AD), plant height (PH), ear position (EPO), and ear height (EH)) under different soil nitrogen regimes, four F3 maize populations were evaluated in Kenya and Zimbabwe. GY and all the traits evaluated showed significant genotypic variance and moderate heritability under both optimum and low nitrogen stress conditions. A total of 91 quantitative trait loci (QTL) related to GY (11) and other secondary traits (AD (26), PH (19), EH (24), EPO (7) and ASI (4)) were detected. Under low soil nitrogen conditions, PH and ASI had the highest number of QTLs. Furthermore, some common QTLs were identified between secondary traits under both nitrogen regimes. These QTLs are of significant value for further validation and possible rapid introgression into maize populations using marker-assisted selection. Identification of many QTL with minor effects indicates genomic selection (GS) is more appropriate for their improvement. Genomic prediction within each population revealed low to moderately high accuracy under optimum and low soil N stress management. However, the accuracies were higher for GY, PH and EH under optimum compared to low soil N stress. Our findings indicate that genetic gain can be improved in maize breeding for low N stress tolerance by using GS.

Physio-biochemical, agronomical, and gene expression analysis reveals different responsive approach to low nitrogen in contrasting rice cultivars for nitrogen use efficiency

BACKGROUND

Nitrogen (N) is an essential macronutrient for plant growth and development as it is an essential constituent of biomolecules. Its availability directly impacts crop yield. Increased N application in crop fields has caused environmental and health problems, and decreasing nitrogen inputs are in demand to maintain crop production sustainability. Understanding the molecular mechanism of N utilization could play a crucial role in improving the nitrogen use efficiency (NUE) of crop plants.

METHODS AND RESULTS

In the present study, the effect of low N supply on plant growth, physio-biochemical, chlorophyll fluorescence attributes, yield components, and gene expression analysis were measured at six developmental stages in rice cultivars. Two rice cultivars were grown with a supply of optimium (120 kg ha^-1) and low N (60 kg ha^-1). Cultivar Vikramarya excelled Aditya at low N supply, and exhibits enhanced plant growth, physiological efficiency, agronomic efficiency, and improved NUE due to higher N uptake and utilization at low N treatment. Moreover, plant biomass, leaf area, and photosynthetic rate were significantly higher in cv. Vikramarya than cv. Aditya at different growth stages, under low N treatment. In addition, enzymatic activities in cultivar Vikramarya were higher than cultivar Aditya under low nitrogen, indicating its greater potential for N metabolism. Gene expression analysis was carried out for the most important nitrogen assimilatory enzymes, such as nitrate reductase (NR), nitrite reductase (NiR), glutamine synthetase (GS), and glutamate synthase (GOGAT). Expression levels of these genes at different growth stages were significantly higher in cv. Vikramarya compared to cv. Aditya at low N supply. Our findings suggest that improving NUE needs specific revision in N metabolism and physiological assimilation.

CONCLUSION

Overall differences in plant growth, physiological efficiency, biochemical activities, and expression levels of N metabolism genes in N-efficient and N-inefficient rice cultivars need a specific adaptation to N metabolism. Regulatory genes may separately or in conjunction, enhance the NUE. These results provide a platform for selecting crop cultivars for nitrogen utilization efficiency at low N treatment.

Efficiency of Nitrogen Use in Sunflower

The large variation in the response of sunflower to nitrogen fertilization indicates the need for studies to better adjust the optimum levels of this nutrient for production conditions. Our objectives were to analyze the agronomic yield of sunflower cultivars as a function of nitrogen fertilization; indicate the cultivar with high nitrogen use efficiency; and measure the adequate N dose for sunflower through nutritional efficiency. The completely randomized block design with split plots was used to conduct the experiments. The treatments included five nitrogen rates being allocated in the plots and the four sunflower cultivars. To estimate the nutrient use efficiency in the sunflower, we measured agronomic efficiency (AE), physiological efficiency (PE), agrophysiological efficiency (APE), apparent recovery efficiency (ARE), and utilization efficiency (UE). The results indicate that all cultivars had a reduction in AE due to the increase in N doses in the first crop. For PE, the highest values were observed for Altis 99 during the 2016 harvest. In that same harvest, Altis 99 had the highest APE. The dose of 30 kg ha−1 provided greater ARE for all cultivars in both crops, with greater emphasis on BRS 122 and Altis 99. The cultivation of cultivars Altis 99 and Multissol at a dose of 30 kg ha−1 in is recommended semiarid regions.

zmm28 transgenic maize increases both N uptake- and N utilization-efficiencies

Biotechnology has emerged as a valuable tool in the development of maize (Zea mays L.) hybrids with enhanced nitrogen (N) use efficiency. Recent work has described the positive effects of an increased and extended expression of the zmm28 transcription factor (Event DP202216) on maize yield productivity. In this study, we expand on the previous findings studying maize N uptake and utilization in DP202216 transgenic hybrids compared to wild-type (WT) controls. Isotope ¹⁵N labeling demonstrates that DP202216 hybrids have an improved N uptake during late-vegetative stages (inducing N storage in lower leaves of the canopy) and, thus, N uptake efficiency (N uptake to applied N ratio) relative to WT. Through both greater N harvest index and reproductive N remobilization, transgenic plants were able to achieve better N utilization efficiency (yield to N uptake ratio). Our findings suggest the DP202216 trait could open new avenues for improving N uptake and utilization efficiencies in maize.

Genetic Architecture of Grain Yield-Related Traits in Sorghum and Maize

Grain size, grain number per panicle, and grain weight are crucial determinants of yield-related traits in cereals. Understanding the genetic basis of grain yield-related traits has been the main research object and nodal in crop science. Sorghum and maize, as very close C4 crops with high photosynthetic rates, stress tolerance and large biomass characteristics, are extensively used to produce food, feed, and biofuels worldwide. In this review, we comprehensively summarize a large number of quantitative trait loci (QTLs) associated with grain yield in sorghum and maize. We placed great emphasis on discussing 22 fine-mapped QTLs and 30 functionally characterized genes, which greatly hinders our deep understanding at the molecular mechanism level. This review provides a general overview of the comprehensive findings on grain yield QTLs and discusses the emerging trend in molecular marker-assisted breeding with these QTLs.

The recent evolutionary rescue of a staple crop depended on over half a century of global germplasm exchange

Rapid environmental change can lead to population extinction or evolutionary rescue. The global staple crop sorghum (Sorghum bicolor) has recently been threatened by a global outbreak of an aggressive new biotype of sugarcane aphid (SCA; Melanaphis sacchari). We characterized genomic signatures of adaptation in a Haitian breeding population that had rapidly adapted to SCA infestation, conducting evolutionary population genomics analyses on 296 Haitian lines versus 767 global accessions. Genome scans and geographic analyses suggest that SCA adaptation has been conferred by a globally rare East African allele of RMES1, which spread to breeding programs in Africa, Asia, and the Americas. De novo genome sequencing revealed potential causative variants at RMES1. Markers developed from the RMES1 sweep predicted resistance in eight independent commercial and public breeding programs. These findings demonstrate the value of evolutionary genomics to develop adaptive trait technology and highlight the benefits of global germplasm exchange to facilitate evolutionary rescue.

Targeting Nitrogen Metabolism and Transport Processes to Improve Plant Nitrogen Use Efficiency

In agricultural cropping systems, relatively large amounts of nitrogen (N) are applied for plant growth and development, and to achieve high yields. However, with increasing N application, plant N use efficiency generally decreases, which results in losses of N into the environment and subsequently detrimental consequences for both ecosystems and human health. A strategy for reducing N input and environmental losses while maintaining or increasing plant performance is the development of crops that effectively obtain, distribute, and utilize the available N. Generally, N is acquired from the soil in the inorganic forms of nitrate or ammonium and assimilated in roots or leaves as amino acids. The amino acids may be used within the source organs, but they are also the principal N compounds transported from source to sink in support of metabolism and growth. N uptake, synthesis of amino acids, and their partitioning within sources and toward sinks, as well as N utilization within sinks represent potential bottlenecks in the effective use of N for vegetative and reproductive growth. This review addresses recent discoveries in N metabolism and transport and their relevance for improving N use efficiency under high and low N conditions.

Nitrogen Fertilizer Induced Alterations in The Root Proteome of Two Rice Cultivars

Nitrogen (N) is an essential nutrient for plants and a key limiting factor of crop production. However, excessive application of N fertilizers and the low nitrogen use efficiency (NUE) have brought in severe damage to the environment. Therefore, improving NUE is urgent and critical for the reductions of N fertilizer pollution and production cost. In the present study, we investigated the effects of N nutrition on the growth and yield of the two rice (Oryza sativa L.) cultivars, conventional rice Huanghuazhan and indica hybrid rice Quanliangyou 681, which were grown at three levels of N fertilizer (including 135, 180 and 225 kg/hm², labeled as N9, N12, N15, respectively). Then, a proteomic approach was employed in the roots of the two rice cultivars treated with N fertilizer at the level of N15. A total of 6728 proteins were identified, among which 6093 proteins were quantified, and 511 differentially expressed proteins were found in the two rice cultivars after N fertilizer treatment. These differentially expressed proteins were mainly involved in ammonium assimilation, amino acid metabolism, carbohydrate metabolism, lipid metabolism, signal transduction, energy production/regulation, material transport, and stress/defense response. Together, this study provides new insights into the regulatory mechanism of nitrogen fertilization in cereal crops.

Determination of the [15N]-Nitrate/[14N]-Nitrate Ratio in Plant Feeding Studies by GC⁻MS

Feeding experiments with stable isotopes are helpful tools for investigation of metabolic fluxes and biochemical pathways. For assessing nitrogen metabolism, the heavier nitrogen isotope, [¹⁵N], has been frequently used. In plants, it is usually applied in form of [¹⁵N]-nitrate, which is assimilated mainly in leaves. Thus, methods for quantification of the [¹⁵N]-nitrate/[¹⁴N]-nitrate ratio in leaves are useful for the planning and evaluation of feeding and pulse–chase experiments. Here we describe a simple and sensitive method for determining the [¹⁵N]-nitrate to [¹⁴N]-nitrate ratio in leaves. Leaf discs (8 mm diameter, approximately 10 mg fresh weight) were sufficient for analysis, allowing a single leaf to be sampled multiple times. Nitrate was extracted with hot water and derivatized with mesitylene in the presence of sulfuric acid to nitromesitylene. The derivatization product was analyzed by gas chromatography–mass spectrometry with electron ionization. Separation of the derivatized samples required only 6 min. The method shows excellent repeatability with intraday and interday standard deviations of less than 0.9 mol%. Using the method, we show that [¹⁵N]-nitrate declines in leaves of hydroponically grown Crassocephalum crepidioides, an African orphan crop, with a biological half-life of 4.5 days after transfer to medium containing [¹⁴N]-nitrate as the sole nitrogen source.

Multi-trait multi-environment Bayesian model reveals G x E interaction for nitrogen use efficiency components in tropical maize

Identifying maize inbred lines that are more efficient in nitrogen (N) use is an important strategy and a necessity in the context of environmental and economic impacts attributed to the excessive N fertilization. N-uptake efficiency (NUpE) and N-utilization efficiency (NUtE) are components of N-use efficiency (NUE). Despite the most maize breeding data have a multi-trait structure, they are often analyzed under a single-trait framework. We aimed to estimate the genetic parameters for NUpE and NUtE in contrasting N levels, in order to identify superior maize inbred lines, and to propose a Bayesian multi-trait multi-environment (MTME) model. Sixty-four tropical maize inbred lines were evaluated in two experiments: at high (HN) and low N (LN) levels. The MTME model was compared to single-trait multi-environment (STME) models. Based on deviance information criteria (DIC), both multi- and single-trait models revealed genotypes x environments (G x E) interaction. In the MTME model, NUpE was found to be weakly heritable with posterior modes of heritability of 0.016 and 0.023 under HN and LN, respectively. NUtE at HN was found to be highly heritable (0.490), whereas under LN condition it was moderately heritable (0.215). We adopted the MTME model, since combined analysis often presents more accurate breeding values than single models. Superior inbred lines for NUpE and NUtE were identified and this information can be used to plan crosses to obtain maize hybrids that have superior nitrogen use efficiency.

Dissection of Resistance Genes to Pseudomonas syringae pv. phaseolicola in UI3 Common Bean Cultivar

Few quantitative trait loci have been mapped for resistance to Pseudomonas syringae pv. phaseolicola in common bean. Two F₂ populations were developed from the host differential UI3 cultivar. The objective of this study was to further characterize the resistance to races 1, 5, 7 and 9 of Psp included in UI3. Using a QTL mapping approach, 16 and 11 main-effect QTLs for pod and primary leaf resistance were located on LG10, explaining up to 90% and 26% of the phenotypic variation, respectively. The homologous genomic region corresponding to primary leaf resistance QTLs detected tested positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL), Natural Resistance Associated Macrophage (NRAMP) and Pentatricopeptide Repeat family (PPR) proteins. It is worth noting that the main effect QTLs for resistance in pod were located inside a 3.5 Mb genomic region that included the Phvul.010G021200 gene, which encodes a protein that has the highest sequence similarity to the RIN4 gene of Arabidopsis, and can be considered an important candidate gene for the organ-specific QTLs identified here. These results support that resistance to Psp from UI3 might result from the immune response activated by combinations of R proteins, and suggest the guard model as an important mechanism in pod resistance to halo blight. The candidate genes identified here warrant functional studies that will help in characterizing the actual defense gene(s) in UI3 genotype.

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.

Maize Plant Resilience to N Stress and Post-silking N Capacity Changes over Time: A Review

We conducted a synthesis analysis on data from 86 published field experiments conducted from 1903 to 2014 to explore the specific consequences of post-silking N accumulation (PostN) in New Era vs. Old Era hybrids on grain yield (GY) and recovery from plant N stress at flowering (R1 stage). The Old Era encompassed studies using genotypes released before, and including, 1990 and the New Era included all studies using genotypes released from 1991 to 2014. Mean N fertilizer rates for experiments in the Old and New Era were similar (170 and 172 kg ha(-1), respectively), but plant densities averaged 5.0 plants m(-2) in the Old Era vs. 7.3 plants m(-2) in the New Era studies. Whole-plant N stress at R1 for each hybrid, environment and management combination was ranked into one of three categories relative to the N Nutrition Index (NNI). The key findings from this analysis are: (i) New Era genotypes increased the proportion of the total plant N at maturity accumulated post-silking (%PostN) as N stress levels at R1 increased-demonstrating improved adaptability to low N environments, (ii) New Era hybrids maintained similar GY on a per plant basis under both low and high N stress at R1 despite being subject to much higher population stress, (iii) PostN is more strongly correlated to GY (both eras combined) when under severe R1 N stress than under less acute N stress at R1, (iv) the New Era accumulated more total N (an increase of 30 kg N ha(-1)) and higher %PostN (an increase from 30% in Old to 36% in New Era), and (v) the change in stover dry weight from silking to physiological maturity (ΔStover) has a positive, linear relationship with PostN in the Old Era but less so in the New Era. This increased understanding of how modern genotypes accumulate more N in the reproductive stage and have more PostN and GY resilience to mid-season N stress, even when grown at much higher plant densities, will assist trait selection and N management research directed to improving maize yields and N efficiencies simultaneously.

Yield QTLome distribution correlates with gene density in maize

The genetic control of yield and related traits in maize has been addressed by many quantitative trait locus (QTL) studies, which have produced a wealth of QTL information, also known as QTLome. In this study, we assembled a yield QTLome database and carried out QTL meta-analysis based on 44 published studies, representing 32 independent mapping populations and 49 parental lines. A total of 808 unique QTLs were condensed to 84 meta-QTLs and were projected on the 10 maize chromosomes. Seventy-four percent of QTLs showed a proportion of phenotypic variance explained (PVE) smaller than 10% confirming the high genetic complexity of grain yield. Yield QTLome projection on the genetic map suggested pericentromeric enrichment of QTLs. Conversely, pericentromeric depletion of QTLs was observed when the physical map was considered, suggesting gene density as the main driver of yield QTL distribution on chromosomes. Dominant and overdominant yield QTLs did not distribute differently from additive effect QTLs.

Association Analysis for Bacterial Spot Resistance in a Directionally Selected Complex Breeding Population of Tomato

Bacterial spot of tomato is caused by at least four species of Xanthomonas with multiple physiological races. We developed a complex breeding population for simultaneous discovery of marker-trait linkage, validation of existing quantitative trait loci (QTL), and pyramiding of resistance. Six advanced accessions with resistance from distinct sources were crossed in all combinations and their F1 hybrids were intercrossed. Over 1,100 segregating progeny were evaluated in the field following inoculation with X. euvesicatoria race T1 strains. We selected 5% of the most resistant and 5% of the most susceptible progeny for evaluation as plots in two subsequent replicated field trials inoculated with T1 and T3 (X. perforans) strains. The estimated heritability of T1 resistance was 0.32. In order to detect previously reported resistance genes, as well as novel QTL, we explored methods to correct for population structure and analysis based on single markers or haplotypes. Both single-point and haplotype analyses identified strong associations in the genomic regions known to carry Rx-3 (chromosome 5) and Rx-4/Xv3 (chromosome 11). Accounting for kinship and structure generally improved the fit of statistical models. Detection of known loci was improved by adding kinship or a combination of kinship and structure using a Q matrix from model-based clustering. Additional QTL were detected on chromosomes 1, 4, 6, and 7 for T1 resistance and chromosomes 2, 4, and 6 for T3 resistance (P < 0.01). Haplotype analysis improved our ability to trace the origin of positive alleles. These results demonstrate that both known and novel associations can be identified using complex breeding populations that have experienced directional selection.

Genetic approaches to enhancing nitrogen-use efficiency (NUE) in cereals: challenges and future directions

Over 100million tonnes of nitrogen (N) fertiliser are applied globally each year to maintain high yields in agricultural crops. The rising price of N fertilisers has made them a major cost for farmers. Inefficient use of N fertiliser leads to substantial environmental problems through contamination of air and water resources and can be a significant economic cost. Consequently, there is considerable need to improve the way N fertiliser is used in farming systems. The efficiency with which crops use applied N fertiliser - the nitrogen-use efficiency (NUE) - is currently quite low for cereals. This is the case in both high yielding environments and lower yielding environments characteristic of cereal growing regions of Australia. Multiple studies have attempted to identify the genetic basis of NUE, but the utility of the results is limited because of the complex nature of the trait and the magnitude of genotype by environment interaction. Transgenic approaches have been applied to improve plant NUE but with limited success, due, in part, to a combination of the complexity of the trait but also due to lack of accurate phenotyping methods. This review documents these two approaches and suggests future directions in improving cereal NUE with a focus on the Australian cereal industry.

Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays

BACKGROUND

Maize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize.

RESULTS

We produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping.

CONCLUSIONS

We demonstrate MAGIC maize's value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers.

A genetic relationship between nitrogen use efficiency and seedling root traits in maize as revealed by QTL analysis

That root system architecture (RSA) has an essential role in nitrogen acquisition is expected in maize, but the genetic relationship between RSA and nitrogen use efficiency (NUE) traits remains to be elucidated. Here, the genetic basis of RSA and NUE traits was investigated in maize using a recombination inbred line population that was derived from two lines contrasted for both traits. Under high-nitrogen and low-nitrogen conditions, 10 NUE- and 9 RSA-related traits were evaluated in four field environments and three hydroponic experiments, respectively. In contrast to nitrogen utilization efficiency (NutE), nitrogen uptake efficiency (NupE) had significant phenotypic correlations with RSA, particularly the traits of seminal roots (r = 0.15-0.31) and crown roots (r = 0.15-0.18). A total of 331 quantitative trait loci (QTLs) were detected, including 184 and 147 QTLs for NUE- and RSA-related traits, respectively. These QTLs were assigned into 64 distinct QTL clusters, and ~70% of QTLs for nitrogen-efficiency (NUE, NupE, and NutE) coincided in clusters with those for RSA. Five important QTLs clusters at the chromosomal regions bin1.04, 2.04, 3.04, 3.05/3.06, and 6.07/6.08 were found in which QTLs for both traits had favourable effects from alleles coming from the large-rooted and high-NupE parent. Introgression of these QTL clusters in the advanced backcross-derived lines conferred mean increases in grain yield of ~14.8% for the line per se and ~15.9% in the testcross. These results reveal a significant genetic relationship between RSA and NUE traits, and uncover the most promising genomic regions for marker-assisted selection of RSA to improve NUE in maize.

Nitrogen availability regulates proline and ethylene production and alleviates salinity stress in mustard (Brassica juncea)

Proline content and ethylene production have been shown to be involved in salt tolerance mechanisms in plants. To assess the role of nitrogen (N) in the protection of photosynthesis under salt stress, the effect of N (0, 5, 10, 20 mM) on proline and ethylene was studied in mustard (Brassica juncea). Sufficient N (10 mM) optimized proline production under non-saline conditions through an increase in proline-metabolizing enzymes, leading to osmotic balance and protection of photosynthesis through optimal ethylene production. Excess N (20 mM), in the absence of salt stress, inhibited photosynthesis and caused higher ethylene evolution but lower proline production compared to sufficient N. In contrast, under salt stress with an increased demand for N, excess N optimized ethylene production, which regulates the proline content resulting in recovered photosynthesis. The effect of excess N on photosynthesis under salt stress was further substantiated by the application of the ethylene biosynthesis inhibitor, 1-aminoethoxy vinylglycine (AVG), which inhibited proline production and photosynthesis. Without salt stress, AVG promoted photosynthesis in plants receiving excess N by inhibiting stress ethylene production. The results suggest that a regulatory interaction exists between ethylene, proline and N for salt tolerance. Nitrogen differentially regulates proline production and ethylene formation to alleviate the adverse effect of salinity on photosynthesis in mustard.

Selection for silage yield and composition did not affect genomic diversity within the Wisconsin Quality Synthetic maize population

Maize silage is forage of high quality and yield, and represents the second most important use of maize in the United States. The Wisconsin Quality Synthetic (WQS) maize population has undergone five cycles of recurrent selection for silage yield and composition, resulting in a genetically improved population. The application of high-density molecular markers allows breeders and geneticists to identify important loci through association analysis and selection mapping, as well as to monitor changes in the distribution of genetic diversity across the genome. The objectives of this study were to identify loci controlling variation for maize silage traits through association analysis and the assessment of selection signatures and to describe changes in the genomic distribution of gene diversity through selection and genetic drift in the WQS recurrent selection program. We failed to find any significant marker-trait associations using the historical phenotypic data from WQS breeding trials combined with 17,719 high-quality, informative single nucleotide polymorphisms. Likewise, no strong genomic signatures were left by selection on silage yield and quality in the WQS despite genetic gain for these traits. These results could be due to the genetic complexity underlying these traits, or the role of selection on standing genetic variation. Variation in loss of diversity through drift was observed across the genome. Some large regions experienced much greater loss in diversity than what is expected, suggesting limited recombination combined with small populations in recurrent selection programs could easily lead to fixation of large swaths of the genome.

Nitrogen stress-induced alterations in the leaf proteome of two wheat varieties grown at different nitrogen levels

Inorganic nitrogen (N) is a key limiting factor of the agricultural productivity. Nitrogen utilization efficiency has significant impact on crop growth and yield as well as on the reduction in production cost. The excessive nitrogen application is accompanied with severe negative impact on environment. Thus to reduce the environmental contamination, improving NUE is need of an hour. In our study we have deployed comparative proteome analysis using 2-DE to investigate the effect of the nitrogen nutrition on differential expression pattern of leaf proteins in low-N sensitive and low-N tolerant wheat (Triticum aestivum L.) varieties. Results showed a comprehensive picture of the post-transcriptional response to different nitrogen regimes administered which would be expected to serve as a basic platform for further characterization of gene function and regulation. We detected proteins related to photosynthesis, glycolysis, nitrogen metabolism, sulphur metabolism and defence. Our results provide new insights towards the altered protein pattern in response to N stress. Through this study we suggest that genes functioning in many physiological events coordinate the response to availability of nitrogen and also for the improvement of NUE of crops.

Association analysis of single nucleotide polymorphisms in candidate genes with root traits in maize (Zea mays L.) seedlings

Several genes involved in maize root development have been isolated. Identification of SNPs associated with root traits would enable the selection of maize lines with better root architecture that might help to improve N uptake, and consequently plant growth particularly under N deficient conditions. In the present study, an association study (AS) panel consisting of 74 maize inbred lines was screened for seedling root traits in 6, 10, and 14-day-old seedlings. Allele re-sequencing of candidate root genes Rtcl, Rth3, Rum1, and Rul1 was also carried out in the same AS panel lines. All four candidate genes displayed different levels of nucleotide diversity, haplotype diversity and linkage disequilibrium. Gene based association analyses were carried out between individual polymorphisms in candidate genes, and root traits measured in 6, 10, and 14-day-old maize seedlings. Association analyses revealed several polymorphisms within the Rtcl, Rth3, Rum1, and Rul1 genes associated with seedling root traits. Several nucleotide polymorphisms in Rtcl, Rth3, Rum1, and Rul1 were significantly (P<0.05) associated with seedling root traits in maize suggesting that all four tested genes are involved in the maize root development. Thus considerable allelic variation present in these root genes can be exploited for improving maize root characteristics.

Three vibrio-resistance related EST-SSR markers revealed by selective genotyping in the clam Meretrix meretrix

The clam Meretrix meretrix is an important commercial bivalve distributed in the coastal areas of South and Southeast Asia. In this study, marker-trait association analyses were performed based on the stock materials of M. meretrix with different vibrio-resistance profile obtained by selective breeding. Forty-eight EST-SSR markers were screened and 27 polymorphic SSRs of them were genotyped in the clam stocks with different resistance to Vibrio parahaemolyticus (11-R and 11-S) and to Vibrio harveyi (09-R and 09-C). Allele frequency distributions of the SSRs among different stocks were compared using Pearson's Chi-square test, and three functional EST-SSR markers (MM959, MM4765 and MM8364) were found to be associated with vibrio-resistance trait. The 140-bp allele of MM959 and 128-bp allele of MM4765 had significantly higher frequencies in resistant groups (11-R and 09-R) than in susceptive/control groups (11-S and 09-C) (P < 0.01), which suggested that the clams carrying these two alleles have stronger resistance against vibrio. Clam individuals of 11-S were divided into three subgroups based on the survival time post-challenge, and the multi-dimensional scaling (MDS) analysis showed that clusters generated by genetic similarity revealed by the three SSR markers were consistent with the three subgroups distinctions. The putative functions of contig959, contig4765 and contig8364 also suggested that the three SSR-involved genes might play important roles in immunity of M. meretrix. All these results supported that EST-SSR markers MM959, MM4765 and MM8364 were associated with vibrio-resistance and would be useful for marker-assisted selection (MAS) in M. meretrix genetic breeding.

Three EST-SSR markers associated with QTL for the growth of the clam Meretrix meretrix revealed by selective genotyping

The clam Meretrix meretrix is a member of widely cultured, commercially important clams. A marker-trait association analysis was performed using expressed sequence tag (EST) simple sequence repeat (SSR) markers for marker-assisted selection in M. meretrix. Three markers, MM1272, MM2034, and MM7721, were found to be significantly associated with quantitative trait loci (QTLs) controlling shell length (P < 0.0001) in clams of a fast-growing population (JSF) and a control population (JSC). The 144-bp allele of MM1272, the 154-bp allele of MM2034, and the 152- and 165-bp alleles of MM7721 showed a significantly higher frequency in the JSF population (17.65, 36.41, 28.67, and 29.33 %) than in the JSC population (4.65, 8.33, 3.47, and 5.56 %). The three markers showed lower values for the number of alleles and observed heterozygosity as well as a higher proportion of homozygotes in JSF than in JSC population. The three markers have been further confirmed in the high and low tails of another population (09G₃SPSB); similarly, lower values for the number of alleles and observed heterozygosity as well as a higher proportion of homozygotes were found in 09G₃SPSB(H). The putative functions of the three gene fragments containing MM1272, MM2034, and MM7721 also suggested that the three SSR-containing genes might be involved in growth of M. meretrix. All the results suggest that the three EST-SSR markers associated with growth QTLs would be useful for marker-assisted selection in M. meretrix breeding.

Proteomic analysis for low and high nitrogen-responsive proteins in the leaves of rice genotypes grown at three nitrogen levels

Nitrogen (N) is an essential nutrient for plants. Increase in crop production is associated with increase in N fertilizers. Excessive use of N fertilizers and the low nitrogen utilization efficiency by crop plants is a major cause for environmental damage. Therefore, to reduce the N-fertilizer pollution, there is an urgent need to improve nitrogen use efficiency. Identification and/or development of genotypes which can grow and yield well at low nitrogen levels may provide a solution. Understanding the molecular mechanism of differential nitrogen use efficiency of the genotypes may provide some clues. Keeping the above facts in mind, in this study we have identified the high N-responsive and low N-responsive contrasting rice genotypes, out of 20 genotypes that were grown at low (1 mM), moderate (10 mM), and high (25 mM) levels of N (KNO(3)). Proteome analysis of leaves revealed that the proteins involved in the energy production/regulation and metabolism in plant leaf tissues are differentially expressed under N treatments. Moreover, some disease-resistant and stress-induced proteins were found to be overexpressed at high levels of N. The present study could be useful in identifying proteins responding to different levels of nitrogen fertilization, which may open new avenues for a better understanding of N use efficiency, and for developing new strategies to enhance N efficiency in cereal crops.

Plant nitrogen assimilation and use efficiency

Crop productivity relies heavily on nitrogen (N) fertilization. Production and application of N fertilizers consume huge amounts of energy, and excess is detrimental to the environment; therefore, increasing plant N use efficiency (NUE) is essential for the development of sustainable agriculture. Plant NUE is inherently complex, as each step-including N uptake, translocation, assimilation, and remobilization-is governed by multiple interacting genetic and environmental factors. The limiting factors in plant metabolism for maximizing NUE are different at high and low N supplies, indicating great potential for improving the NUE of current cultivars, which were bred in well-fertilized soil. Decreasing environmental losses and increasing the productivity of crop-acquired N requires the coordination of carbohydrate and N metabolism to give high yields. Increasing both the grain and N harvest index to drive N acquisition and utilization are important approaches for breeding future high-NUE cultivars.

Nitrogen-efficient rice cultivars can reduce nitrate pollution

INTRODUCTION

Environmental pollution by un-utilized nitrogenous fertilizer at the agricultural field is one of the key issues of the day. Rice-based cropping system, the mainstay of Indian agriculture, is one of the main sources of unused N-fertilizer since rice utilizes only 30-40% of total applied N, and the rest goes to waste and creates environmental as well as economic loss.

METHODS

Identification of rice genotypes that can grow and yield well at low nitrogen levels is highly desirable for enhancement of nitrogen use efficiency (NUE). In the present study, we have identified large variability in the NUE of rice cultivars on the basis of plant with low, medium, and high levels of N in nutrient solution. To establish the basis of this wide variability in NUE, nitrate uptake kinetics and enzymes of nitrate assimilation were studied.

RESULTS AND DISCUSSION

The data of nitrate uptake kinetics revealed that the nitrate uptake is mediated by low-affinity transporter system (LATS) in N-inefficient rice cultivars and by both LATS and high-affinity transporter systems (HATS) in N-efficient genotypes. Activities of nitrate reductase, nitrite reductase, glutamine synthetase, glutamate synthase, and the soluble protein content were found to be increased in moderately N-efficient and low N-efficient cultivars with increase in external supply of nitrogen. However, a non-significant decrease in these enzymes was recorded in high N-efficient cultivars with the increase in N supply.

CONCLUSIONS

This study suggests that the HATS, high NR, and glutamine synthetase activity and the soluble protein content distribution have a key role in N efficiency of rice genotypes. These parameters may be considered in breeding and genetic engineering programs for improving the NUE of rice, which might be helpful in reducing the fertilizer loss, hence decreasing environmental degradation and improving crop productivity through improvement of nitrogen utilization efficiency in rice.

Root-specific reduction of cytokinin causes enhanced root growth, drought tolerance, and leaf mineral enrichment in Arabidopsis and tobacco

Optimizing root system architecture can overcome yield limitations in crop plants caused by water or nutrient shortages. Classic breeding approaches are difficult because the trait is governed by many genes and is difficult to score. We generated transgenic Arabidopsis thaliana and tobacco (Nicotiana tabacum) plants with enhanced root-specific degradation of the hormone cytokinin, a negative regulator of root growth. These transgenic plants form a larger root system, whereas growth and development of the shoot are similar. Elongation of the primary root, root branching, and root biomass formation were increased by up to 60% in transgenic lines, increasing the root-to-shoot ratio. We thus demonstrated that a single dominant gene could regulate a complex trait, root growth. Moreover, we showed that cytokinin regulates root growth in a largely organ-autonomous fashion that is consistent with its dual role as a hormone with both paracrine and long-distance activities. Transgenic plants had a higher survival rate after severe drought treatment. The accumulation of several elements, including S, P, Mn, Mg, Zn, as well as Cd from a contaminated soil, was significantly increased in shoots. Under conditions of sulfur or magnesium deficiency, leaf chlorophyll content was less affected in transgenic plants, demonstrating the physiological relevance of shoot element accumulation. Our approach might contribute to improve drought tolerance, nutrient efficiency, and nutrient content of crop plants.

Fine-mapping of qRL6.1, a major QTL for root length of rice seedlings grown under a wide range of NH4(+) concentrations in hydroponic conditions

Root system development is an important target for improving yield in cereal crops. Active root systems that can take up nutrients more efficiently are essential for enhancing grain yield. In this study, we attempted to identify quantitative trait loci (QTL) involved in root system development by measuring root length of rice seedlings grown in hydroponic culture. Reliable growth conditions for estimating the root length were first established to renew nutrient solutions daily and supply NH4(+) as a single nitrogen source. Thirty-eight chromosome segment substitution lines derived from a cross between 'Koshihikari', a japonica variety, and 'Kasalath', an indica variety, were used to detect QTL for seminal root length of seedlings grown in 5 or 500 microM NH4(+). Eight chromosomal regions were found to be involved in root elongation. Among them, the most effective QTL was detected on a 'Kasalath' segment of SL-218, which was localized to the long-arm of chromosome 6. The 'Kasalath' allele at this QTL, qRL6.1, greatly promoted root elongation under all NH4(+) concentrations tested. The genetic effect of this QTL was confirmed by analysis of the near-isogenic line (NIL) qRL6.1. The seminal root length of the NIL was 13.5-21.1% longer than that of 'Koshihikari' under different NH4(+) concentrations. Toward our goal of applying qRL6.1 in a molecular breeding program to enhance rice yield, a candidate genomic region of qRL6.1 was delimited within a 337 kb region in the 'Nipponbare' genome by means of progeny testing of F2 plants/F3 lines derived from a cross between SL-218 and 'Koshihikari'.

Genetic dissection of nitrogen nutrition in pea through a QTL approach of root, nodule, and shoot variability

Pea (Pisum sativum L.) is the third most important grain legume worldwide, and the increasing demand for protein-rich raw material has led to a great interest in this crop as a protein source. Seed yield and protein content in crops are strongly determined by nitrogen (N) nutrition, which in legumes relies on two complementary pathways: absorption by roots of soil mineral nitrogen, and fixation in nodules of atmospheric dinitrogen through the plant-Rhizobium symbiosis. This study assessed the potential of naturally occurring genetic variability of nodulated root structure and functioning traits to improve N nutrition in pea. Glasshouse and field experiments were performed on seven pea genotypes and on the 'Cameor' x 'Ballet' population of recombinant inbred lines selected on the basis of parental contrast for root and nodule traits. Significant variation was observed for most traits, which were obtained from non-destructive kinetic measurements of nodulated root and shoot in pouches, root and shoot image analysis, (15)N quantification, or seed yield and protein content determination. A significant positive relationship was found between nodule establishment and root system growth, both among the seven genotypes and the RIL population. Moreover, several quantitative trait loci for root or nodule traits and seed N accumulation were mapped in similar locations, highlighting the possibility of breeding new pea cultivars with increased root system size, sustained nodule number, and improved N nutrition. The impact on both root or nodule traits and N nutrition of the genomic regions of the major developmental genes Le and Af was also underlined.

Nitrogen metabolism in the developing ear of maize (Zea mays): analysis of two lines contrasting in their mode of nitrogen management

*The main steps of nitrogen (N) metabolism were characterized in the developing ear of the two maize (Zea mays) lines F2 and Io, which were previously used to investigate the genetic basis of nitrogen use efficiency (NUE) in relation to yield. *During the grain-filling period, we monitored changes in metabolite content, enzyme activities and steady-state levels of transcripts for marker genes of amino acid synthesis and interconversion in the cob and the kernels. *Under low N fertilization conditions, line Io accumulated glutamine, asparagine and alanine preferentially in the developing kernels, whereas in line F2, glutamine and proline were the predominant amino acids. Quantification of the mRNA-encoding enzymes involved in asparagine, alanine and proline biosynthesis confirmed that the differences observed between the two lines at the physiological level are likely to be attributable to enhanced expression of the cognate genes. *Integrative analysis of physiological and gene expression data indicated that the developing ear of line Io had higher N use and transport capacities than line F2. Thus, in maize there is genetic and environmental control of N metabolism not only in vegetative source organs but also in reproductive sink organs.

Root based approaches to improving nitrogen use efficiency in plants

In the majority of agricultural growing regions, crop production is highly dependent on the supply of exogenous nitrogen (N) fertilizers. Traditionally, this dependency and the use of N-fertilizers to restore N depleted soils has been rewarded with increased plant health and yields. In recent years, increased competition for non-renewable fossil fuel reserves has directly elevated prices of N-fertilizers and the cost of agricultural production worldwide. Furthermore, N-fertilizer based pollution is becoming a serious issue for many regions where agriculture is highly concentrated. To help minimize the N footprint associated with agricultural production there is significant interest at the plant level to develop technologies which can allow economically viable production while using less applied N. To complement recent reviews examining N utilization efficiency in agricultural plants, this review will explore those strategies operating specifically at the root level, which may directly contribute to improved N use efficiencies in agricultural crops such as cereals, where the majority of N-fertilizers are used and lost to the environment. Root specific phenotypes that will be addressed in the context of improvements to N acquisition and assimilation efficiencies include: root morphology; root to shoot ratios; root vigour, root length density; and root N transport and metabolism.

Adjustment of growth and central metabolism to a mild but sustained nitrogen-limitation in Arabidopsis

We have established a simple soil-based experimental system that allows a small and sustained restriction of growth of Arabidopsis by low nitrogen (N). Plants were grown in a large volume of a peat-vermiculite mix that contained very low levels of inorganic N. As a control, inorganic N was added in solid form to the peat-vermiculite mix, or plants were grown in conventional nutrient-rich solids. The low N growth regime led to a sustained 20% decrease of the relative growth rate over a period of 2 weeks, resulting in a two- to threefold decrease in biomass in 35- to 40-day-old plants. Plants in the low N regime contained lower levels of nitrate, lower nitrate reductase activity, lower levels of malate, fumarate and other organic acids and slightly higher levels of starch, as expected from published studies of N-limited plants. However, their rosette protein content was unaltered, and total and many individual amino acid levels increased compared with N-replete plants. This metabolic phenotype reveals that Arabidopsis responds adaptively to low N by decreasing the rate of growth, while maintaining the overall protein content, and maintaining or even increasing the levels of many amino acids.

Genetic engineering of improved nitrogen use efficiency in rice by the tissue-specific expression of alanine aminotransferase

Summary Nitrogen is quantitatively the most essential nutrient for plants and a major factor limiting crop productivity. One of the critical steps limiting the efficient use of nitrogen is the ability of plants to acquire it from applied fertilizer. Therefore, the development of crop plants that absorb and use nitrogen more efficiently has been a long-term goal of agricultural research. In an attempt to develop nitrogen-efficient plants, rice (Oryza sativa L.) was genetically engineered by introducing a barley AlaAT (alanine aminotransferase) cDNA driven by a rice tissue-specific promoter (OsAnt1). This modification increased the biomass and grain yield significantly in comparison with control plants when plants were well supplied with nitrogen. Compared with controls, transgenic rice plants also demonstrated significant changes in key metabolites and total nitrogen content, indicating increased nitrogen uptake efficiency. The development of crop plants that take up and assimilate nitrogen more efficiently would not only improve the use of nitrogen fertilizers, resulting in lower production costs, but would also have significant environmental benefits. These results are discussed in terms of their relevance to the development of strategies to engineer enhanced nitrogen use efficiency in crop plants.

Selection mapping of loci for quantitative disease resistance in a diverse maize population

The selection response of a complex maize population improved primarily for quantitative disease resistance to northern leaf blight (NLB) and secondarily for common rust resistance and agronomic phenotypes was investigated at the molecular genetic level. A tiered marker analysis with 151 simple sequence repeat (SSR) markers in 90 individuals of the population indicated that on average six alleles per locus were available for selection. An improved test statistic for selection mapping was developed, in which quantitative trait loci (QTL) are identified through the analysis of allele-frequency shifts at mapped multiallelic loci over generations of selection. After correcting for the multiple tests performed, 25 SSR loci showed evidence of selection. Many of the putatively selected loci were unlinked and dispersed across the genome, which was consistent with the diffuse distribution of previously published QTL for NLB resistance. Compelling evidence for selection was found on maize chromosome 8, where several putatively selected loci colocalized with published NLB QTL and a race-specific resistance gene. Analysis of F2 populations derived from the selection mapping population suggested that multiple linked loci in this chromosomal segment were, in part, responsible for the selection response for quantitative resistance to NLB.

Genetic variation for N-remobilization and postsilking N-uptake in a set of maize recombinant inbred lines. 3. QTL detection and coincidences

The objective of this study was to map and characterize QTLs for traits related to nitrogen utilization efficiency (NUE), grain N yield, N-remobilization and post-silking N-uptake. Furthermore, to examine whether QTLs detected with recombinant inbred lines (RILs) crossed to a tester are common to those detected with line per se evaluation, both types of evaluations were developed from the same set of RILs. The material was studied over two years at high N-input, and one year at low N-input. We used (15)N-labelling to evaluate with accuracy the proportion of N remobilized from stover to kernels and the proportion of postsilking N-uptake allocated to kernels. With 59 traits studied in three environments, 608 QTLs were detected. Using a method of QTL clustering, 72 clusters were identified, with few QTLs being specific to one environment or to the type of plant material (lines or testcross families). However, considering each trait separately, few QTLs were common to both line per se and testcross evaluation. This shows that genetic variability is expressed differently according to the type of progeny. Studies of coincidences among QTLs within the clusters showed an antagonism between N-remobilization and N-uptake in several QTL-clusters. QTLs for N-uptake, root system architecture and leaf greenness coincided positively in eight clusters. QTLs for remobilization mainly coincided in clusters with QTLs for leaf senescence. On the whole, sign of coincidences between QTLs underlined the role of a "stay-green" phenotype in favouring N-uptake capacity, and thus grain yield and N grain yield.

Linkage disequilibrium in two European F(2) flint maize populations under modified recurrent full-sib selection

According to quantitative genetic theory, linkage disequilibrium (LD) can hamper the short- and long-term selection response in recurrent selection (RS) programs. We analyzed LD in two European flint maize populations, KW1265 x D146 (A x B) and D145 x KW1292 (C x D), under modified recurrent full-sib selection. Our objectives were to investigate (1) the decay of initial parental LD present in F(2) populations by three generations of intermating, (2) the generation of new LD in four (A x B) and seven (C x D) selection cycles, and (3) the relationship between LD changes and estimates of the additive genetic variance. We analyzed the F(2) and the intermated populations as well as all selection cycles with 104 (A x B) and 101 (C x D) simple sequence repeat (SSR) markers with a uniform coverage of the entire maize genome. The LD coefficient D and the composite LD measure Delta were estimated and significance tests for LD were performed. LD was reduced by intermating as expected from theory. A directional generation of negative LD between favorable alleles could not be observed during the selection cycles. However, considerable undirectional changes in D were observed, which we attributed to genetic sampling due to the finite population size used for recombination. Consequently, a long-term reduction of the additive genetic variance due to negative LD was not observed. Our experimental results support the hypothesis that in practical RS programs with maize, LD generated by selection is not a limiting factor for obtaining a high selection response.

Developmental genes have pleiotropic effects on plant morphology and source capacity, eventually impacting on seed protein content and productivity in pea

Increasing pea (Pisum sativum) seed nutritional value and particularly seed protein content, while maintaining yield, is an important challenge for further development of this crop. Seed protein content and yield are complex and unstable traits, integrating all the processes occurring during the plant life cycle. During filling, seeds are the main sink to which assimilates are preferentially allocated at the expense of vegetative organs. Nitrogen seed demand is satisfied partly by nitrogen acquired by the roots, but also by nitrogen remobilized from vegetative organs. In this study, we evaluated the respective roles of nitrogen source capacity and sink strength in the genetic variability of seed protein content and yield. We showed in eight genotypes of diverse origins that both the maximal rate of nitrogen accumulation in the seeds and nitrogen source capacity varied among genotypes. Then, to identify the genetic factors responsible for seed protein content and yield variation, we searched for quantitative trait loci (QTL) for seed traits and for indicators of sink strength and source nitrogen capacity. We detected 261 QTL across five environments for all traits measured. Most QTL for seed and plant traits mapped in clusters, raising the possibility of common underlying processes and candidate genes. In most environments, the genes Le and Afila, which control internode length and the switch between leaflets and tendrils, respectively, determined plant nitrogen status. Depending on the environment, these genes were linked to QTL of seed protein content and yield, suggesting that source-sink adjustments depend on growing conditions.

Temporal changes in allele frequencies in two European F(2) flint maize populations under modified recurrent full-sib selection

Selection and random genetic drift are the two main forces affecting the selection response of recurrent selection (RS) programs by changes in allele frequencies. Therefore, detailed knowledge on allele frequency changes attributable to these forces is of fundamental importance for assessing RS programs. The objectives of our study were to (1) estimate the number, position, and genetic effect of quantitative trait loci (QTL) for selection index and its components in the base populations, (2) determine changes in allele frequencies of QTL regions due to the effects of random genetic drift and selection, and (3) predict allele frequency changes by using QTL results and compare these predictions with observed values. We performed QTL analyses, based on restriction fragment length polymorphisms (RFLPs) and simple sequence repeats (SSRs), in 274 F(2:3) lines of cross KW1265 x D146 (A x B) and 133 F(3:4) lines of cross D145 x KW1292 (C x D) originating from two European flint maize populations. Four (A x B) and seven (C x D) cycles of RS were analyzed with SSRs for significant allele frequency changes due to selection. Several QTL regions for selection index were detected with simple and composite interval mapping. In some of them, flanking markers showed a significant allele frequency change after the first and the final selection cycles. The correlation between observed and predicted allele frequencies was significant only in A x B. We attribute these observations mainly to (1) the high dependence of the power of QTL detection on the population size and (2) the occurrence of undetectable QTL in repulsion phase. Assessment of allele frequency changes in RS programs can be used to detect marker alleles linked to QTL regions under selection pressure.

Detection of marker-QTL associations by studying change in marker frequencies with selection

The value of selective genotyping for the detection of QTL has already been studied from a theoretical point of view but with the assumption of a negligible contribution (r2P) of the QTL to the phenotypic variance. For predicting change in gene frequency, we show that this assumption is only valid for r2P less than 0.05 and for a proportion selected higher than 1%. Therefore, we develop a study of the optimization of selective genotyping without assumption on QTL effect, with selection either of both tails (bidirectional genotyping or BSG) or only one tail (unidirectional genotyping or USG). For a given population size of phenotyped plants the optimal proportion selected for selective genotyping is around 30% for each tail. For the same investment as in ANOVA, by investing more in phenotyping than in genotyping when the cost ratio of genotyping to phenotyping is higher than 1, the optimal proportion selected appears to be between 10 and 20% for each tail. It is mainly affected by the cost ratio and decreases when the cost ratio increases. At this optimum, BSG is competitive with ANOVA, or even more powerful, when the cost ratio is higher than 1. USG can also be competitive when the cost ratio is higher than 2. Using experimental data from two populations of about 300 F4 inbred families of maize, it was verified that BSG at the optimum gives the same results as ANOVA or is better whereas USG is less powerful or equivalent.