Field high-throughput phenotyping: the new crop breeding frontier

Constraints in field phenotyping capability limit our ability to dissect the genetics of quantitative traits, particularly those related to yield and stress tolerance (e.g., yield potential as well as increased drought, heat tolerance, and nutrient efficiency, etc.). The development of effective field-based high-throughput phenotyping platforms (HTPPs) remains a bottleneck for future breeding advances. However, progress in sensors, aeronautics, and high-performance computing are paving the way. Here, we review recent advances in field HTPPs, which should combine at an affordable cost, high capacity for data recording, scoring and processing, and non-invasive remote sensing methods, together with automated environmental data collection. Laboratory analyses of key plant parts may complement direct phenotyping under field conditions. Improvements in user-friendly data management together with a more powerful interpretation of results should increase the use of field HTPPs, therefore increasing the efficiency of crop genetic improvement to meet the needs of future generations.

Conventional digital cameras as a tool for assessing leaf area index and biomass for cereal breeding

Affordable and easy-to-use methods for assessing biomass and leaf area index (LAI) would be of interest in most breeding programs. Here, we describe the evaluation of a protocol for photographic sampling and image analysis aimed at providing low-labor yet robust indicators of biomass and LAI. In this trial, two genotypes of triticale, two of bread wheat, and four of tritordeum were studied. At six dates during the growing cycle, biomass and LAI were measured destructively, and digital photography was taken on the same dates. Several vegetation indices were calculated from each image. The results showed that repeatable and consistent values of the indices were obtained in consecutive photographic samplings on the same plots. The photographic indices were highly correlated with the destructive measurements, though the magnitude of the correlation was lower after anthesis. This work shows that photographic assessment of biomass and LAI can be fast, affordable, have good repeatability, and can be used under bright and overcast skies. A practical vegetation index derived from pictures is the fraction of green pixels over the total pixels of the image, and as it shows good correlations with all biomass variables, is the most robust to lighting conditions and has easy interpretation.

Source/sink interactions underpin crop yield: the case for trehalose 6-phosphate/SnRK1 in improvement of wheat

Considerable interest has been evoked by the analysis of the regulatory pathway in carbohydrate metabolism and cell growth involving the non-reducing disaccharide trehalose (TRE). TRE is at small concentrations in mesophytes such as Arabidopsis thaliana and Triticum aestivum, excluding a role in osmoregulation once suggested for it. Studies of TRE metabolism, and genetic modification of it, have shown a very wide and more important role of the pathway in regulation of many processes in development, growth, and photosynthesis. It has now been established that rather than TRE, it is trehalose 6-phosphate (T6P) which has such profound effects. T6P is the intermediary in TRE synthesis formed from glucose-6-phosphate and UDP-glucose, derived from sucrose, by the action of trehalose phosphate synthase. The concentration of T6P is determined both by the rate of synthesis, which depends on the sucrose concentration, and also by the rate of breakdown by trehalose-6-phosphate phosphatase which produces TRE. Changing T6P concentrations by genetically modifying the enzymes of synthesis and breakdown has altered photosynthesis, sugar metabolism, growth, and development which affect responses to, and recovery from, environmental factors. Many of the effects of T6P on metabolism and growth occur via the interaction of T6P with the SnRK1 protein kinase system. T6P inhibits the activity of SnRK1, which de-represses genes encoding proteins involved in anabolism. Consequently, a large concentration of sucrose increases T6P and thereby inhibits SnRK1, so stimulating growth of cells and their metabolic activity. The T6P/SnRK1 mechanism offers an important new view of how the distribution of assimilates to organs, such as developing grains in cereal plants, is achieved. This review briefly summarizes the factors determining, and limiting, yield of wheat (particularly mass/grain which is highly conserved) and considers how T6P/SnRK1 might function to determine grain yield and might be altered to increase them. Increasing the potential rate of filling and mass/grain are ways in which total crop yield could be increased with good husbandry which maintains crop assimilation Cereal yields globally are not increasing, despite the greater production required to meet human demand. Careful targeting of T6P is showing much promise for optimization of source/sink for yield improvement and offers yet further possibilities for increasing sink demand and grain size in wheat.

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.

Next generation characterisation of cereal genomes for marker discovery

Cereal crops form the bulk of the world’s food sources, and thus their importance cannot be understated. Crop breeding programs increasingly rely on high-resolution molecular genetic markers to accelerate the breeding process. The development of these markers is hampered by the complexity of some of the major cereal crop genomes, as well as the time and cost required. In this review, we address current and future methods available for the characterisation of cereal genomes, with an emphasis on faster and more cost effective approaches for genome sequencing and the development of markers for trait association and marker assisted selection (MAS) in crop breeding programs.

SNP discovery by illumina-based transcriptome sequencing of the olive and the genetic characterization of Turkish olive genotypes revealed by AFLP, SSR and SNP markers

Background

The olive tree (Olea europaea L.) is a diploid (2n = 2x = 46) outcrossing species mainly grown in the Mediterranean area, where it is the most important oil-producing crop. Because of its economic, cultural and ecological importance, various DNA markers have been used in the olive to characterize and elucidate homonyms, synonyms and unknown accessions. However, a comprehensive characterization and a full sequence of its transcriptome are unavailable, leading to the importance of an efficient large-scale single nucleotide polymorphism (SNP) discovery in olive. The objectives of this study were (1) to discover olive SNPs using next-generation sequencing and to identify SNP primers for cultivar identification and (2) to characterize 96 olive genotypes originating from different regions of Turkey.

Methodology/Principal Findings

Next-generation sequencing technology was used with five distinct olive genotypes and generated cDNA, producing 126,542,413 reads using an Illumina Genome Analyzer IIx. Following quality and size trimming, the high-quality reads were assembled into 22,052 contigs with an average length of 1,321 bases and 45 singletons. The SNPs were filtered and 2,987 high-quality putative SNP primers were identified. The assembled sequences and singletons were subjected to BLAST similarity searches and annotated with a Gene Ontology identifier. To identify the 96 olive genotypes, these SNP primers were applied to the genotypes in combination with amplified fragment length polymorphism (AFLP) and simple sequence repeats (SSR) markers.

Conclusions/Significance

This study marks the highest number of SNP markers discovered to date from olive genotypes using transcriptome sequencing. The developed SNP markers will provide a useful source for molecular genetic studies, such as genetic diversity and characterization, high density quantitative trait locus (QTL) analysis, association mapping and map-based gene cloning in the olive. High levels of genetic variation among Turkish olive genotypes revealed by SNPs, AFLPs and SSRs allowed us to characterize the Turkish olive genotype.

Identification of drought tolerance markers in a diverse population of rice cultivars by expression and metabolite profiling

Rice provides about half of the calories consumed in Asian countries, but its productivity is often reduced by drought, especially when grown under rain-fed conditions. Cultivars with increased drought tolerance have been bred over centuries. Slow selection for drought tolerance on the basis of phenotypic traits may be accelerated by using molecular markers identified through expression and metabolic profiling. Previously, we identified 46 candidate genes with significant genotype × environment interaction in an expression profiling study on four cultivars with contrasting drought tolerance. These potential markers and in addition GC-MS quantified metabolites were tested in 21 cultivars from both indica and japonica background that varied in drought tolerance. Leaf blades were sampled from this population of cultivars grown under control or long-term drought condition and subjected to expression analysis by qRT-PCR and metabolite profiling. Under drought stress, metabolite levels correlated mainly negatively with performance parameters, but eight metabolites correlated positively. For 28 genes, a significant correlation between expression level and performance under drought was confirmed. Negative correlations were predominant. Among those with significant positive correlation was the gene coding for a cytosolic fructose-1,6-bisphosphatase. This enzyme catalyzes a highly regulated step in C-metabolism. The metabolic and transcript marker candidates for drought tolerance were identified in a highly diverse population of cultivars. Thus, these markers may be used to select for tolerance in a wide range of rice germplasms.

Drought tolerance in modern and wild wheat

The genus Triticum includes bread (Triticum aestivum) and durum wheat (Triticum durum) and constitutes a major source for human food consumption. Drought is currently the leading threat on world's food supply, limiting crop yield, and is complicated since drought tolerance is a quantitative trait with a complex phenotype affected by the plant's developmental stage. Drought tolerance is crucial to stabilize and increase food production since domestication has limited the genetic diversity of crops including wild wheat, leading to cultivated species, adapted to artificial environments, and lost tolerance to drought stress. Improvement for drought tolerance can be achieved by the introduction of drought-grelated genes and QTLs to modern wheat cultivars. Therefore, identification of candidate molecules or loci involved in drought tolerance is necessary, which is undertaken by "omics" studies and QTL mapping. In this sense, wild counterparts of modern varieties, specifically wild emmer wheat (T. dicoccoides), which are highly tolerant to drought, hold a great potential. Prior to their introgression to modern wheat cultivars, drought related candidate genes are first characterized at the molecular level, and their function is confirmed via transgenic studies. After integration of the tolerance loci, specific environment targeted field trials are performed coupled with extensive analysis of morphological and physiological characteristics of developed cultivars, to assess their performance under drought conditions and their possible contributions to yield in certain regions. This paper focuses on recent advances on drought related gene/QTL identification, studies on drought related molecular pathways, and current efforts on improvement of wheat cultivars for drought tolerance.

Searching for novel sources of field resistance to Ug99 and Ethiopian stem rust races in durum wheat via association mapping

Puccinia graminis f. sp. tritici, the causative agent of stem rust in wheat, is a devastating disease of durum wheat. While more than 50 stem rust resistance (Sr) loci have been identified in wheat, only a few of them have remained effective against Ug99 (TTKSK race) and other durum-specific Ethiopian races. An association mapping (AM) approach based on 183 diverse durum wheat accessions was utilized to identify resistance loci for stem rust response in Ethiopia over four field-evaluation seasons and artificial inoculation with Ug99 and a mixture of durum-specific races. The panel was profiled with simple sequence repeat, Diversity Arrays Technology and sequence-tagged site markers (1,253 in total). The resistance turned out to be oligogenic, with twelve QTL-tagging markers that were significant (P < 0.05) across three or four seasons. R (2) values ranged from 1.1 to 11.3 %.Twenty-four additional single-marker/QTL regions were found to be significant over two seasons. The AM results confirmed the role of Sr13, previously described in bi-parental mapping studies, and the role of chromosome regions putatively harbouring Sr9, Sr14, Sr17 and Sr28. Three minor QTLs were coincident with those reported in hexaploid wheat and five overlapped with those recently reported in the Sebatel × Kristal durum mapping population. Thirteen single-marker/QTL regions were located in chromosome regions where no Sr genes/QTLs have been previously reported. The allelic variation identified in this study is readily available and can be exploited for marker-assisted selection, thus providing additional opportunities for a more durable stem rust resistance under field conditions.

Short, natural, and extended photoperiod response in BC2F4 lines of bread wheat with different photoperiod-1 (Ppd-1) alleles

Flowering is a critical period in the life cycle of flowering plant species, resulting in an irreversible commitment of significant resources. Wheat is photoperiod sensitive, flowering only when daylength surpasses a critical length; however, photoperiod insensitivity (PI) has been selected by plant breeders for >40 years to enhance yield in certain environments. Control of flowering time has been greatly facilitated by the development of molecular markers for the Photoperiod-1 (Ppd-1) homeoloci, on the group 2 chromosomes. In the current study, an allelic series of BC2F4 lines in the winter wheat cultivars 'Robigus' and 'Alchemy' was developed to elucidate the influence on flowering of eight gene variants from the B- and D-genomes of bread wheat and the A-genome of durum wheat. Allele effects were tested in short, natural, and extended photoperiods in the field and controlled environments. Across genetic background and treatment, the D-genome PI allele, Ppd-D1a, had a more potent effect on reducing flowering time than Ppd-B1a. However, there was significant donor allele effect for both Ppd-D1a and Ppd-B1a, suggesting the presence of linked modifier genes and/or additional sources of latent sensitivity. Development of Ppd-A1a BC2F4 lines derived from synthetic hexaploid wheat provided an opportunity to compare directly the flowering time effect of the A-genome allele from durum with the B- and D-genome variants from bread wheat for the first time. Analyses indicated that the reducing effect of Ppd-A1a is comparable with that of Ppd-D1a, confirming it as a useful alternative source of PI.

Genetic dissection of growth traits in a Chinese indigenous × commercial broiler chicken cross

Background

In China, consumers often prefer indigenous broiler chickens over commercial breeds, as they have characteristic meat qualities requested within traditional culinary customs. However, the growth-rate of these indigenous breeds is slower than that of the commercial broilers, which means they have not yet reached their full economic value. Therefore, combining the valuable meat quality of the native chickens with the efficiency of the commercial broilers is of interest. In this study, we generated an F₂ intercross between the slow growing native broiler breed, Huiyang Beard chicken, and the fast growing commercial broiler breed, High Quality chicken Line A, and used it to map loci explaining the difference in growth rate between these breeds.

Results

A genome scan to identify main-effect loci affecting 24 growth-related traits revealed nine distinct QTL on six chromosomes. Many QTL were pleiotropic and conformed to the correlation patterns observed between phenotypes. Most of the mapped QTL were found in locations where growth QTL have been reported in other populations, although the effects were greater in this population. A genome scan for pairs of interacting loci identified a number of additional QTL in 10 other genomic regions. The epistatic pairs explained 6–8% of the residual phenotypic variance. Seven of the 10 epistatic QTL mapped in regions containing candidate genes in the ubiquitin mediated proteolysis pathway, suggesting the importance of this pathway in the regulation of growth in this chicken population.

Conclusions

The main-effect QTL detected using a standard one-dimensional genome scan accounted for a significant fraction of the observed phenotypic variance in this population. Furthermore, genes in known pathways present interesting candidates for further exploration. This study has thus located several QTL regions as promising candidates for further study, which will increase our understanding of the genetic mechanisms underlying growth-related traits in chickens.

Multi-environment analysis and improved mapping of a yield-related QTL on chromosome 3B of wheat

Improved mapping, multi-environment quantitative trait loci (QTL) analysis and dissection of allelic effects were used to define a QTL associated with grain yield, thousand grain weight and early vigour on chromosome 3BL of bread wheat (Triticum aestivum L.) under abiotic stresses. The QTL had pleiotropic effects and showed QTL x environment interactions across 21 diverse environments in Australia and Mexico. The occurrence and the severity of water deficit combined with high temperatures during the growing season affected the responsiveness of this QTL, resulting in a reversal in the direction of allelic effects. The influence of this QTL can be substantial, with the allele from one parent (RAC875) increasing grain yield by up to 12.5 % (particularly in environments where both heat and drought stress occurred) and the allele from the other parent (Kukri) increasing grain yield by up to 9 % in favourable environments. With the application of additional markers and the genotyping of additional recombinant inbred lines, the genetic map in the QTL region was refined to provide a basis for future positional cloning.

Plant response to environmental conditions: assessing potential production, water demand, and negative effects of water deficit

This paper reviews methods for analyzing plant performance and its genetic variability under a range of environmental conditions. Biomass accumulation is linked every day to available light in the photosynthetically active radiation (PAR) domain, multiplied by the proportion of light intercepted by plants and by the radiation use efficiency. Total biomass is cumulated over the duration of the considered phase (e.g., plant cycle or vegetative phase). These durations are essentially constant for a given genotype provided that time is corrected for temperature (thermal time). Several ways of expressing thermal time are reviewed. Two alternative equations are presented, based either on the effect of transpiration, or on yield components. Their comparative interests and drawbacks are discussed. The genetic variability of each term of considered equations affects yield under water deficit, via mechanisms at different scales of plant organization and time. The effect of any physiological mechanism on yield of stressed plants acts via one of these terms, although the link is not always straightforward. Finally, I propose practical ways to compare the productivity of genotypes in field environments, and a "minimum dataset" of environmental data and traits that should be recorded for that.

Future scenarios for plant phenotyping

With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to accurately measure increasingly large numbers of plants and plant parameters. The goal is to provide quantitative analyses of plant structure and function relevant for traits that help plants better adapt to low-input agriculture and resource-limited environments. We provide an overview of the inherently multidisciplinary research in plant phenotyping, focusing on traits that will assist in selecting genotypes with increased resource use efficiency. We highlight opportunities and challenges for integrating noninvasive or minimally invasive technologies into screening protocols to characterize plant responses to environmental challenges for both controlled and field experimentation. Although technology evolves rapidly, parallel efforts are still required because large-scale phenotyping demands accurate reporting of at least a minimum set of information concerning experimental protocols, data management schemas, and integration with modeling. The journey toward systematic plant phenotyping has only just begun.

Plant response to environmental conditions: assessing potential production, water demand, and negative effects of water deficit

This paper reviews methods for analyzing plant performance and its genetic variability under a range of environmental conditions. Biomass accumulation is linked every day to available light in the photosynthetically active radiation (PAR) domain, multiplied by the proportion of light intercepted by plants and by the radiation use efficiency. Total biomass is cumulated over the duration of the considered phase (e.g., plant cycle or vegetative phase). These durations are essentially constant for a given genotype provided that time is corrected for temperature (thermal time). Several ways of expressing thermal time are reviewed. Two alternative equations are presented, based either on the effect of transpiration, or on yield components. Their comparative interests and drawbacks are discussed. The genetic variability of each term of considered equations affects yield under water deficit, via mechanisms at different scales of plant organization and time. The effect of any physiological mechanism on yield of stressed plants acts via one of these terms, although the link is not always straightforward. Finally, I propose practical ways to compare the productivity of genotypes in field environments, and a "minimum dataset" of environmental data and traits that should be recorded for that.

Deposition and residues of azoxystrobin and imidacloprid on greenhouse lettuce with implications for human consumption

Lettuce greenhouse experiments were carried out from March to June 2011 in order to analyze how pesticides behave from the time of application until their intake via human consumption taking into account the primary distribution of pesticides, field dissipation, and post-harvest processing. In addition, experimental conditions were used to evaluate a new dynamic plant uptake model comparing its results with the experimentally derived residues. One application of imidacloprid and two of azoxystrobin were conducted. For evaluating primary pesticide distribution, two approaches based on leaf area index and vegetation cover were used and results were compared with those obtained from a tracer test. High influence of lettuce density, growth stage and type of sprayer was observed in primary distribution showing that low densities or early growth stages implied high losses of pesticides on soil. Washed and unwashed samples of lettuce were taken and analyzed from application to harvest to evaluate removal of pesticides by food processing. Results show that residues found on the Spanish preharvest interval days were in all cases below officially set maximum residue limits, although it was observed that time between application and harvest is as important for residues as application amounts. An overall reduction of 40-60% of pesticides residues was obtained from washing lettuce. Experimentally derived residues were compared with modeled residues and deviate from 1.2 to 1.4 for imidacloprid and azoxystrobin, respectively, presenting good model predictions. Resulting human intake fractions range from 0.045 kg(intake) kg(applied)(-1) for imidacloprid to 0.14 kg(intake) kg(applied)(-1) for azoxystrobin.

Phenotyping for drought tolerance of crops in the genomics era

Improving crops yield under water-limited conditions is the most daunting challenge faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly pivotal role for the selection of drought-resilient genotypes and, more in general, for a meaningful dissection of the quantitative genetic landscape that underscores the adaptive response of crops to drought. A major and universally recognized obstacle to a more effective translation of the results produced by drought-related studies into improved cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to identify the quantitative trait loci that govern yield and related traits across different water regimes. This review provides basic principles and a broad set of references useful for the management of phenotyping practices for the study and genetic dissection of drought tolerance and, ultimately, for the release of drought-tolerant cultivars.

Integrated genomics, physiology and breeding approaches for improving drought tolerance in crops

Drought is one of the most serious production constraint for world agriculture and is projected to worsen with anticipated climate change. Inter-disciplinary scientists have been trying to understand and dissect the mechanisms of plant tolerance to drought stress using a variety of approaches; however, success has been limited. Modern genomics and genetic approaches coupled with advances in precise phenotyping and breeding methodologies are expected to more effectively unravel the genes and metabolic pathways that confer drought tolerance in crops. This article discusses the most recent advances in plant physiology for precision phenotyping of drought response, a vital step before implementing the genetic and molecular-physiological strategies to unravel the complex multilayered drought tolerance mechanism and further exploration using molecular breeding approaches for crop improvement. Emphasis has been given to molecular dissection of drought tolerance by QTL or gene discovery through linkage and association mapping, QTL cloning, candidate gene identification, transcriptomics and functional genomics. Molecular breeding approaches such as marker-assisted backcrossing, marker-assisted recurrent selection and genome-wide selection have been suggested to be integrated in crop improvement strategies to develop drought-tolerant cultivars that will enhance food security in the context of a changing and more variable climate.

AB-QTL analysis reveals new alleles associated to proline accumulation and leaf wilting under drought stress conditions in barley (Hordeum vulgare L.)

BACKGROUND

Land plants have evolved several measures to maintain their life against abiotic stresses. The accumulation of proline is the most generalized response of plants under drought, heat or salt stress conditions. It is known as an osmoprotectant which also acts as an instant source of energy during drought recovery process. But, both its role and genetic inheritance are poorly understood in agriculture crops. In the present work, advanced backcross quantitative trait locus (AB-QTL) analysis was performed to elucidate genetic mechanisms controlling proline accumulation and leaf wilting in barley under drought stress conditions.

RESULTS

The analysis revealed eight QTL associated to proline content (PC) and leaf wilting (WS). QTL for PC were localized on chromosome 3H, 4H, 5H and 6H. The strongest QTL effect QPC.S42.5H was detected on chromosome 5H where drought inducible exotic allele was associated to increase PC by 54%. QTL effects QPC.S42.3H, QPC.S42.4H and QPC.S42.6H were responsible to heighten PC due to the preeminence of elite alleles over the exotic alleles which ranged from 26% to 43%. For WS, QTL have been localized on chromosome 1H, 2H, 3H and 4H. Among these, QWS.S42.1H and QWS.S42.4H were associated to decrease in WS due to the introgression of exotic alleles. In addition, two digenic epistatic interaction effects were detected for WS where the additive effect of exotic alleles imparted a favorable increase in the trait value.

CONCLUSIONS

The present data represents a first report on whole-genome mapping of proline accumulation and leaf wilting in barley. The detected QTL are linked to new alleles from both cultivated and wild accessions which bring out an initial insight on the genetic inheritance of PC and WS. These QTL alleles are fixed in the isogenic background of Scarlett, which will allow for positional cloning of underlying genes and to develop drought resilient barley cultivars.

Genetic dissection of grain yield and physical grain quality in bread wheat (Triticum aestivum L.) under water-limited environments

In the water-limited bread wheat production environment of southern Australia, large advances in grain yield have previously been achieved through the introduction and improved understanding of agronomic traits controlled by major genes, such as the semi-dwarf plant stature and photoperiod insensitivity. However, more recent yield increases have been achieved through incremental genetic advances, of which, breeders and researchers do not fully understand the underlying mechanism(s). A doubled haploid population was utilised, derived from a cross between RAC875, a relatively drought-tolerant breeders' line and Kukri, a locally adapted variety more intolerant of drought. Experiments were performed in 16 environments over four seasons in southern Australia, to physiologically dissect grain yield and to detect quantitative trait loci (QTL) for these traits. Two stage multi-environment trial analysis identified three main clusters of experiments (forming distinctive environments, ENVs), each with a distinctive growing season rainfall patterns. Kernels per square metre were positively correlated with grain yield and influenced by kernels per spikelet, a measure of fertility. QTL analysis detected nine loci for grain yield across these ENVs, individually accounting for between 3 and 18% of genetic variance within their respective ENVs, with the RAC875 allele conferring increased grain yield at seven of these loci. These loci were partially dissected by the detection of co-located QTL for other traits, namely kernels per square metre. While most loci for grain yield have previously been reported, their deployment and effect within local germplasm are now better understood. A number of novel loci can be further exploited to aid breeders' efforts in improving grain yield in the southern Australian environment.

Root traits and δ13C and δ18O of durum wheat under different water regimes

Plant growth, root characteristics and the stable carbon (δ13C) and oxygen (δ18O) composition were studied in durum wheat. Four recombinant inbred lines with good agronomic adaptation were grown under well watered (WW) and water stress (WS) conditions until mid-grain filling in lysimeters. Gas exchange was measured in the flag leaf just before harvest and then the aerial dry matter (Aerial DM), root weight density (RWD) and root length density (RLD) and the specific root length (SRL) were evaluated and the δ13C and δ18O of the roots, the flag leaf blade and the spike were analysed. Water stress decreased stomatal conductance, plant accumulated transpiration and Aerial DM, whereas δ13C and δ18O increased. Genotypic differences were found for all gas-exchange and root traits and isotope signatures. Aerial DM was positively correlated with RLD, regardless of the water regime, whereas it was negatively correlated with δ13C and δ18O, but only under WW conditions. Moreover, RWD and RLD were negatively related to both δ13C and δ18O under the WW regime, but no clear pattern existed under WS. Our study supports the use of δ13C and δ18O as proxies for selecting root traits associated with higher growth in the absence of water stress.

Development of a deletion and genetic linkage map for the 5A and 5B chromosomes of wheat (Triticum aestivum)

The aims of the present study were to provide deletion maps for wheat ( Triticum aestivum L.) chromosomes 5A and 5B and a detailed genetic map of chromosome 5A enriched with popular microsatellite markers, which could be compared with other existing maps and useful for mapping major genes and quantitative traits loci (QTL). Physical mapping of 165 gSSR and EST-SSR markers was conducted by amplifying each primer pair on Chinese Spring, aneuploid lines, and deletion lines for the homoeologous group 5 chromosomes. A recombinant inbred line (RIL) mapping population that is recombinant for only chromosome 5A was obtained by crossing the wheat cultivar Chinese Spring and the disomic substitution line Chinese Spring-5A dicoccoides and was used to develop a genetic linkage map of chromosome 5A. A total of 67 markers were found polymorphic between the parental lines and were mapped in the RIL population. Sixty-three loci and the Q gene were clustered in three linkage groups ordered at a minimum LOD score of 5, while four loci remained unlinked. The whole genetic 5A chromosome map covered 420.2 cM, distributed among three linkage groups of 189.3, 35.4, and 195.5 cM. The EST sequences located on chromosomes 5A and 5B were used for comparative analysis against Brachypodium distachyon (L.) P. Beauv. and rice ( Oryza sativa L.) genomes to resolve orthologous relationships among the genomes of wheat and the two model species.

High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield.

Genomic associations for drought tolerance on the short arm of wheat chromosome 4B

Drought is a major constraint to maintaining yield stability of wheat in rain fed and limited irrigation agro-ecosystems. Genetic improvement for drought tolerance in wheat has been difficult due to quantitative nature of the trait involving multiple genes with variable effects and lack of effective selection strategies employing molecular markers. Here, a framework molecular linkage map was constructed using 173 DNA markers randomly distributed over the 21 wheat chromosomes. Grain yield and other drought-responsive shoot and root traits were phenotyped for 2 years under drought stress and well-watered conditions on a mapping population of recombinant inbred lines (RILs) derived from a cross between drought-sensitive semidwarf variety "WL711" and drought-tolerant traditional variety "C306". Thirty-seven genomics region were identified for 10 drought-related traits at 18 different chromosomal locations but most of these showed small inconsistent effects. A consistent genomic region associated with drought susceptibility index (qDSI.4B.1) was mapped on the short arm of chromosome 4B, which also controlled grain yield per plant, harvest index, and root biomass under drought. Transcriptome profiling of the parents and two RIL bulks with extreme phenotypes revealed five genes underlying this genomic region that were differentially expressed between the parents as well as the two RIL bulks, suggesting that they are likely candidates for drought tolerance. Syntenic genomic regions of barley, rice, sorghum, and maize genomes were identified that also harbor genes for drought tolerance. Markers tightly linked to this genomic region in combination with other important regions on group 7 chromosomes may be used in marker-assisted breeding for drought tolerance in wheat.

Phenotyping for abiotic stress tolerance in maize

The ability to quickly develop germplasm having tolerance to several complex polygenic inherited abiotic and biotic stresses combined is critical to the resilience of cropping systems in the face of climate change. Molecular breeding offers the tools to accelerate cereal breeding; however, suitable phenotyping protocols are essential to ensure that the much-anticipated benefits of molecular breeding can be realized. To facilitate the full potential of molecular tools, greater emphasis needs to be given to reducing the within-experimental site variability, application of stress and characterization of the environment and appropriate phenotyping tools. Yield is a function of many processes throughout the plant cycle, and thus integrative traits that encompass crop performance over time or organization level (i.e. canopy level) will provide a better alternative to instantaneous measurements which provide only a snapshot of a given plant process. Many new phenotyping tools based on remote sensing are now available including non-destructive measurements of growth-related parameters based on spectral reflectance and infrared thermometry to estimate plant water status. Here we describe key field phenotyping protocols for maize with emphasis on tolerance to drought and low nitrogen.

Genetic dissection of grain yield and physical grain quality in bread wheat (Triticum aestivum L.) under water-limited environments

In the water-limited bread wheat production environment of southern Australia, large advances in grain yield have previously been achieved through the introduction and improved understanding of agronomic traits controlled by major genes, such as the semi-dwarf plant stature and photoperiod insensitivity. However, more recent yield increases have been achieved through incremental genetic advances, of which, breeders and researchers do not fully understand the underlying mechanism(s). A doubled haploid population was utilised, derived from a cross between RAC875, a relatively drought-tolerant breeders' line and Kukri, a locally adapted variety more intolerant of drought. Experiments were performed in 16 environments over four seasons in southern Australia, to physiologically dissect grain yield and to detect quantitative trait loci (QTL) for these traits. Two stage multi-environment trial analysis identified three main clusters of experiments (forming distinctive environments, ENVs), each with a distinctive growing season rainfall patterns. Kernels per square metre were positively correlated with grain yield and influenced by kernels per spikelet, a measure of fertility. QTL analysis detected nine loci for grain yield across these ENVs, individually accounting for between 3 and 18% of genetic variance within their respective ENVs, with the RAC875 allele conferring increased grain yield at seven of these loci. These loci were partially dissected by the detection of co-located QTL for other traits, namely kernels per square metre. While most loci for grain yield have previously been reported, their deployment and effect within local germplasm are now better understood. A number of novel loci can be further exploited to aid breeders' efforts in improving grain yield in the southern Australian environment.

Genetic insight into yield-associated traits of wheat grown in multiple rain-fed environments

Background

Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL) directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14.

Methodology/Principal Findings

Ten yield-associated traits, including yield per plant (YP), number of spikes per plant (NSP), number of grains per spike (NGS), one-thousand grain weight (TGW), total number of spikelets per spike (TNSS), number of sterile spikelets per spike (NSSS), proportion of fertile spikelets per spike (PFSS), spike length (SL), density of spikelets per spike (DSS) and plant height (PH), were assessed across 14 (for YP) to 23 (for TGW) year × location × water regime environments in China. Then, the genetic effects were partitioned into additive main effects (a), epistatic main effects (aa) and their environment interaction effects (ae and aae) by using composite interval mapping in a mixed linear model.

Conclusions/Significance

Twelve (YP) to 33 (PH) QTLs were identified on all 21 chromosomes except 6D. QTLs were more frequently observed on chromosomes 1B, 2B, 2D, 5A and 6B, and were concentrated in a few regions on individual chromosomes, exemplified by three striking yield-related QTL clusters on chromosomes 2B, 1B and 4B that explained the correlations between YP and other traits. The additive main-effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. Consistent with agronomic analyses, a group of progeny derived by selecting TGW and NGS, with higher grain yield, had an increased frequency of QTL for high YP, NGS, TGW, TNSS, PFSS, SL, PH and fewer NSSS, when compared to low yielding progeny. This indicated that it is feasible by marker-assisted selection to facilitate wheat production.

QTL mapping of physiological traits associated with salt tolerance in Medicago truncatula Recombinant Inbred Lines

In this study, QTL mapping of physiological traits in the model Legume (Medicago truncatula) was performed using a set of RILs derived from LR5. Twelve parameters associated with Na+ and K+ content in leaves, stems and roots were measured. Broad-sense heritability of these traits was ranged from 0.15 to 0.83 in control and from 0.14 to 0.61 in salt stress. Variation among RILs was dependent on line, treatment and line by treatment effect. We mapped 6 QTLs in control, 2 in salt stress and 5 for sensitivity index. No major QTL was identified indicating that tolerance to salt stress is governed by several genes with low effects. Detected QTL for leaf, stem and root traits did not share the same map locations, suggesting that genes controlling transport of Na+ and K+ may be different. The maximum of QTL was observed on chromosome 1, no QTL was detected on chromosomes 5 and 6.

Application of support vector regression to genome-assisted prediction of quantitative traits

A byproduct of genome-wide association studies is the possibility of carrying out genome-enabled prediction of disease risk or of quantitative traits. This study is concerned with predicting two quantitative traits, milk yield in dairy cattle and grain yield in wheat, using dense molecular markers as predictors. Two support vector regression (SVR) models, ε-SVR and least-squares SVR, were explored and compared to a widely applied linear regression model, the Bayesian Lasso, the latter assuming additive marker effects. Predictive performance was measured using predictive correlation and mean squared error of prediction. Depending on the kernel function chosen, SVR can model either linear or nonlinear relationships between phenotypes and marker genotypes. For milk yield, where phenotypes were estimated breeding values of bulls (a linear combination of the data), SVR with a Gaussian radial basis function (RBF) kernel had a slightly better performance than with a linear kernel, and was similar to the Bayesian Lasso. For the wheat data, where phenotype was raw grain yield, the RBF kernel provided clear advantages over the linear kernel, e.g., a 17.5% increase in correlation when using the ε-SVR. SVR with a RBF kernel also compared favorably to the Bayesian Lasso in this case. It is concluded that a nonlinear RBF kernel may be an optimal choice for SVR, especially when phenotypes to be predicted have a nonlinear dependency on genotypes, as it might have been the case in the wheat data.

A common genetic determinism for sensitivities to soil water deficit and evaporative demand: meta-analysis of quantitative trait Loci and introgression lines of maize

Evaporative demand and soil water deficit equally contribute to water stress and to its effect on plant growth. We have compared the genetic architectures of the sensitivities of maize (Zea mays) leaf elongation rate with evaporative demand and soil water deficit. The former was measured via the response to leaf-to-air vapor pressure deficit in well-watered plants, the latter via the response to soil water potential in the absence of evaporative demand. Genetic analyses of each sensitivity were performed over 21 independent experiments with (1) three mapping populations, with temperate or tropical materials, (2) one population resulting from the introgression of a tropical drought-tolerant line in a temperate line, and (3) two introgression libraries genetically independent from mapping populations. A very large genetic variability was observed for both sensitivities. Some lines maintained leaf elongation at very high evaporative demand or water deficit, while others stopped elongation in mild conditions. A complex architecture arose from analyses of mapping populations, with 19 major meta-quantitative trait loci involving strong effects and/or more than one mapping population. A total of 68% of those quantitative trait loci affected sensitivities to both evaporative demand and soil water deficit. In introgressed lines, 73% of the tested genomic regions affected both sensitivities. To our knowledge, this study is the first genetic demonstration that hydraulic processes, which drive the response to evaporative demand, also have a large contribution to the genetic variability of plant growth under water deficit in a large range of genetic material.

Quantitative trait loci and underlying candidate genes controlling agronomical and fruit quality traits in octoploid strawberry (Fragaria × ananassa)

Breeding for fruit quality traits in strawberry (Fragaria × ananassa, 2n = 8x = 56) is complex due to the polygenic nature of these traits and the octoploid constitution of this species. In order to improve the efficiency of genotype selection, the identification of quantitative trait loci (QTL) and associated molecular markers will constitute a valuable tool for breeding programs. However, the implementation of these markers in breeding programs depends upon the complexity and stability of QTLs across different environments. In this work, the genetic control of 17 agronomical and fruit quality traits was investigated in strawberry using a F(1) population derived from an intraspecific cross between two contrasting selection lines, '232' and '1392'. QTL analyses were performed over three successive years based on the separate parental linkage maps and a pseudo-testcross strategy. The integrated strawberry genetic map consists of 338 molecular markers covering 37 linkage groups, thus exceeding the 28 chromosomes. 33 QTLs were identified for 14 of the 17 studied traits and approximately 37% of them were stable over time. For each trait, 1-5 QTLs were identified with individual effects ranging between 9.2 and 30.5% of the phenotypic variation, indicating that all analysed traits are complex and quantitatively inherited. Many QTLs controlling correlated traits were co-located in homoeology group V, indicating linkage or pleiotropic effects of loci. Candidate genes for several QTLs controlling yield, anthocyanins, firmness and L-ascorbic acid are proposed based on both their co-localization and predicted function. We also report conserved QTLs among strawberry and other Rosaceae based on their syntenic location.

Quantitative trait loci and underlying candidate genes controlling agronomical and fruit quality traits in octoploid strawberry (Fragaria × ananassa)

Breeding for fruit quality traits in strawberry (Fragaria × ananassa, 2n = 8x = 56) is complex due to the polygenic nature of these traits and the octoploid constitution of this species. In order to improve the efficiency of genotype selection, the identification of quantitative trait loci (QTL) and associated molecular markers will constitute a valuable tool for breeding programs. However, the implementation of these markers in breeding programs depends upon the complexity and stability of QTLs across different environments. In this work, the genetic control of 17 agronomical and fruit quality traits was investigated in strawberry using a F(1) population derived from an intraspecific cross between two contrasting selection lines, '232' and '1392'. QTL analyses were performed over three successive years based on the separate parental linkage maps and a pseudo-testcross strategy. The integrated strawberry genetic map consists of 338 molecular markers covering 37 linkage groups, thus exceeding the 28 chromosomes. 33 QTLs were identified for 14 of the 17 studied traits and approximately 37% of them were stable over time. For each trait, 1-5 QTLs were identified with individual effects ranging between 9.2 and 30.5% of the phenotypic variation, indicating that all analysed traits are complex and quantitatively inherited. Many QTLs controlling correlated traits were co-located in homoeology group V, indicating linkage or pleiotropic effects of loci. Candidate genes for several QTLs controlling yield, anthocyanins, firmness and L-ascorbic acid are proposed based on both their co-localization and predicted function. We also report conserved QTLs among strawberry and other Rosaceae based on their syntenic location.

Distribution of parental genome blocks in recombinant inbred lines

We consider recombinant inbred lines obtained by crossing two given homozygous parents and then applying multiple generations of self-crossings or full-sib matings. The chromosomal content of any such line forms a mosaic of blocks, each alternatively inherited identically by descent from one of the parents. Quantifying the statistical properties of such mosaic genomes has remained an open challenge for many years. Here, we solve this problem by taking a continuous chromosome picture and assuming crossovers to be noninterfering. Using a continuous-time random walk framework and Markov chain theory, we determine the statistical properties of these identical-by-descent blocks. We find that successive block lengths are only very slightly correlated. Furthermore, the blocks on the ends of chromosomes are larger on average than the others, a feature understandable from the nonexponential distribution of block lengths.

Resistance to Soil-borne cereal mosaic virus in durum wheat is controlled by a major QTL on chromosome arm 2BS and minor loci

Soil-borne cereal mosaic (SBCM) is a viral disease, which seriously affects hexaploid as well as tetraploid wheat crops in Europe. In durum wheat (Triticum durum Desf.), the elite germplasm is characterized by a wide range of responses to SBCMV, from susceptibility to almost complete resistance. In this study, the genetic analysis of SBCMV resistance was carried out using a population of 181 durum wheat recombinant inbred lines (RILs) obtained from Meridiano (resistant) × Claudio (moderately susceptible), which were profiled with SSR and DArT markers. The RILs were characterized for SBCMV response in the field under severe and uniform SBCMV infection during 2007 and 2008. A wide range of disease reactions (as estimated by symptom severity and DAS-ELISA) was observed. A large portion of the variability for SBCMV response was explained by a major QTL (QSbm.ubo-2BS) located in the distal telomeric region of chromosome 2BS near the marker triplet Xbarc35-Xwmc661-Xgwm210, with R(2) values ranging from 51.6 to 91.6%. The favorable allele was contributed by Meridiano. Several QTLs with minor effects on SBCMV response were also detected. Consistently with the observed transgressive segregation, the resistance alleles at minor QTLs were contributed by both parents. The presence and effects of QSbm.ubo-2BS were validated through association mapping in a panel of 111 elite durum wheat accessions.

A dynamic and complex network regulates the heterosis of yield-correlated traits in rapeseed (Brassica napus L.)

Although much research has been conducted, the genetic architecture of heterosis remains ambiguous. To unravel the genetic architecture of heterosis, a reconstructed F₂ population was produced by random intercross among 202 lines of a double haploid population in rapeseed (Brassica napus L.). Both populations were planted in three environments and 15 yield-correlated traits were measured, and only seed yield and eight yield-correlated traits showed significant mid-parent heterosis, with the mean ranging from 8.7% (branch number) to 31.4% (seed yield). Hundreds of QTL and epistatic interactions were identified for the 15 yield-correlated traits, involving numerous variable loci with moderate effect, genome-wide distribution and obvious hotspots. All kinds of mode-of-inheritance of QTL (additive, A; partial-dominant, PD; full-dominant, D; over-dominant, OD) and epistatic interactions (additive × additive, AA; additive × dominant/dominant × additive, AD/DA; dominant × dominant, DD) were observed and epistasis, especially AA epistasis, seemed to be the major genetic basis of heterosis in rapeseed. Consistent with the low correlation between marker heterozygosity and mid-parent heterosis/hybrid performance, a considerable proportion of dominant and DD epistatic effects were negative, indicating heterozygosity was not always advantageous for heterosis/hybrid performance. The implications of our results on evolution and crop breeding are discussed.

Dissection of QTL effects for root traits using a chromosome arm-specific mapping population in bread wheat

A high-resolution chromosome arm-specific mapping population was used in an attempt to locate/detect gene(s)/QTL for different root traits on the short arm of rye chromosome 1 (1RS) in bread wheat. This population consisted of induced homoeologous recombinants of 1RS with 1BS, each originating from a different crossover event and distinct from all other recombinants in the proportions of rye and wheat chromatin present. It provides a simple and powerful approach to detect even small QTL effects using fewer progeny. A promising empirical Bayes method was applied to estimate additive and epistatic effects for all possible marker pairs simultaneously in a single model. This method has an advantage for QTL analysis in minimizing the error variance and detecting interaction effects between loci with no main effect. A total of 15 QTL effects, 6 additive and 9 epistatic, were detected for different traits of root length and root weight in 1RS wheat. Epistatic interactions were further partitioned into inter-genomic (wheat and rye alleles) and intra-genomic (rye-rye or wheat-wheat alleles) interactions affecting various root traits. Four common regions were identified involving all the QTL for root traits. Two regions carried QTL for almost all the root traits and were responsible for all the epistatic interactions. Evidence for inter-genomic interactions is provided. Comparison of mean values supported the QTL detection.

Mapping QTL main and interaction influences on milling quality in elite US rice germplasm

Rice (Oryza sativa L.) head-rice yield (HR) is a key export and domestic quality trait whose genetic control is poorly understood. With the goal of identifying genomic regions influencing HR, quantitative-trait-locus (QTL) mapping was carried out for quality-related traits in recombinant inbred lines (RILs) derived from crosses of common parent Cypress, a high-HR US japonica cultivar, with RT0034, a low-HR indica line (129 RILs) and LaGrue, a low-HR japonica cultivar (298 RILs), grown in two US locations in 2005-2007. Early heading increased HR in the Louisiana (LA) but not the Arkansas (AR) location. Fitting QTL-mapping models to separate QTL main and QTL × environment interaction (QEI) effects and identify epistatic interactions revealed six main-effect HR QTLs in the two crosses, at four of which Cypress contributed the increasing allele. Multi-QTL models accounted for 0.36 of genetic and 0.21 of genetic × environment interaction of HR in MY1, and corresponding proportions of 0.25 and 0.37 in MY2. The greater HR advantage of Cypress in LA than in AR corresponded to a genomewide pattern of opposition of HR-increasing QTL effects by AR-specific effects, suggesting a selection strategy for improving this cultivar for AR. Treating year-location combinations as independent environments resulted in underestimation of QEI effects, evidently owing to lower variation among years within location than between location. Identification of robust HR QTLs in elite long-grain germplasm is suggested to require more detailed attention to the interaction of plant and grain development parameters with environmental conditions than has been given to date.

Population genetics of genomics-based crop improvement methods

Many genome-wide association studies (GWAS) in humans are concluding that, even with very large sample sizes and high marker densities, most of the genetic basis of complex traits may remain unexplained. At the same time, recent research in plant GWAS is showing much greater success with fewer resources. Both GWAS and genomic selection (GS), a method for predicting phenotypes by the use of genome-wide marker data, are receiving considerable attention among plant breeders. In this review we explore how differences in population genetic histories, as well as past selection for traits of interest, have produced trait architectures and patterns of linkage disequilibrium (LD) that frequently differ dramatically between domesticated plants and humans, making detection of quantitative trait loci (QTL) effects in crops more rewarding and less costly than in humans.

Association mapping in durum wheat grown across a broad range of water regimes

Association mapping was used to dissect the genetic basis of drought-adaptive traits and grain yield (GY) in a collection of 189 elite durum wheat accessions evaluated in 15 environments highly different for water availability during the crop cycle (from 146 to 711 mm) and GY (from 9.9 to 67.3 q ha(-1)). For highly heritable traits (e.g. heading date, kernel weight, etc.) several significant experiment-wise marker-trait associations were detected across five or more (up to 13 for kernel weight) environments, with R(2) values ranging from ca. 5 to 10%. As to GY, significant associations (R(2) from 2.5 to 4.2%) were mostly detected in one environment only (56 markers), while decreasing rapidly from two to five environments (from 20 to three markers, respectively) and with only one marker (Xbarc197 on chr. 5A) found significant in six environments (ranging from low- to high-yielding). These results are probably due to the complex genetic basis of GY and its interaction with environmental conditions. The number of markers significantly affecting GY decreased considerably under drought conditions, suggesting a limited effectiveness of association mapping to identify loci for GY under low-moisture conditions, most likely because different genotypes can attain similar phenotypes via different morpho-physiological traits and corresponding gene networks. Our study confirmed the role of major loci for phenology previously described in biparental mapping populations, highlighted a novel set of loci for drought-adaptive traits, and provided information on the agronomic value of the alleles at such loci across a broad range of soil moisture conditions.

Genomic distribution of quantitative trait loci for yield and yield-related traits in common wheat

A major objective of quantitative trait locus (QTL) studies is to find genes/markers that can be used in breeding programs via marker assisted selection (MAS). We surveyed the QTLs for yield and yield-related traits and their genomic distributions in common wheat (Triticum aestivum L.) in the available published reports. We then carried out a meta-QTL (MQTL) analysis to identify the major and consistent QTLs for these traits. In total, 55 MQTLs were identified, of which 12 significant MQTLs were located on wheat chromosomes 1A, 1B, 2A, 2D, 3B, 4A, 4B, 4D and 5A. Our study showed that the genetic control of yield and its components in common wheat involved the important genes such as Rht and Vrn. Furthermore, several significant MQTLs were found in the chromosomal regions corresponding to several rice genomic locations containing important QTLs for yield related traits. Our results demonstrate that meta-QTL analysis is a powerful tool for confirming the major and stable QTLs and refining their chromosomal positions in common wheat, which may be useful for improving the MAS efficiency of yield related traits.

High-throughput shoot imaging to study drought responses

Drought is a complex stress which elicits a wide variety of plant responses. As such, genetic studies of drought are particularly difficult. Elucidation of the genetic basis of components contributing to drought tolerance is likely to be more tractable than that of overall drought tolerance. Certain of the traits which contribute to drought tolerance in plants and the high-throughput phenotyping techniques available to measure those traits are described in this paper. On the basis of the dynamic nature of drought, plant development, and the resulting stress response, the focus is on non-destructive imaging techniques which allow a temporal resolution and monitoring of the same plants throughout the experiment. Information on the physiological changes in response to drought over time is vital in order to identify and characterize different drought-tolerance mechanisms. High-throughput imaging provides a valuable new tool which allows the dissection of plant responses to drought into a series of component traits.

Genetic and genomic tools to improve drought tolerance in wheat

Tolerance to drought is a quantitative trait, with a complex phenotype, often confounded by plant phenology. Breeding for drought tolerance is further complicated since several types of abiotic stress, such as high temperatures, high irradiance, and nutrient toxicities or deficiencies can challenge crop plants simultaneously. Although marker-assisted selection is now widely deployed in wheat, it has not contributed significantly to cultivar improvement for adaptation to low-yielding environments and breeding has relied largely on direct phenotypic selection for improved performance in these difficult environments. The limited success of the physiological and molecular breeding approaches now suggests that a careful rethink is needed of our strategies in order to understand better and breed for drought tolerance. A research programme for increasing drought tolerance of wheat should tackle the problem in a multi-disciplinary approach, considering interaction between multiple stresses and plant phenology, and integrating the physiological dissection of drought-tolerance traits and the genetic and genomics tools, such as quantitative trait loci (QTL), microarrays, and transgenic crops. In this paper, recent advances in the genetics and genomics of drought tolerance in wheat and barley are reviewed and used as a base for revisiting approaches to analyse drought tolerance in wheat. A strategy is then described where a specific environment is targeted and appropriate germplasm adapted to the chosen environment is selected, based on extensive definition of the morpho-physiological and molecular mechanisms of tolerance of the parents. This information was used to create structured populations and develop models for QTL analysis and positional cloning.

Genetic dissection of the developmental behaviours of plant height in wheat under diverse water regimes

Plant height (PH), a crucial trait related to yield potential in crop plants, is known to be typically quantitatively inherited. However, its full expression can be inhibited by a limited water supply. In this study, the genetic basis of the developmental behaviour of PH was assessed in a 150-line wheat (Triticum aestivum L.) doubled haploid population (Hanxuan 10 x Lumai 14) grown in 10 environments (year x site x water regime combinations) by unconditional and conditional quantitative trait locus (QTL) analyses in a mixed linear model. Genes that were expressed selectively during ontogeny were identified. No single QTL was continually active in all periods of PH growth, and QTLs with additive effects (A-QTLs) expressed in the period S1|S0 (the period from the original point to the jointing stage) formed a foundation for PH development. Additive main effects (a effects), which were mostly expressed in S1|S0, were more important than epistatic main effects (aa effects) or QTL x environment interaction (QE) effects, suggesting that S1|S0 was the most significant development period affecting PH growth. A few QTLs, such as QPh.cgb-6B.7, showed high adaptability for water-limited environments. Many QTLs, including four A-QTLs (QPh.cgb-2D.1, QPh.cgb-4B.1, QPh.cgb-4D.1, and QPh.cgb-5A.7) coincident with previously identified reduced height (Rht) genes (Rht8, Rht1, Rht2, and Rht9), interacted with more than one other QTL, indicating that the genetic architecture underlying PH development is a network of genes with additive and epistatic effects. Therefore, based on multilocus combinations in S1|S0, superior genotypes were predicted for guiding improvements in breeding for PH.

Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis

An F(4:5) population of 490 recombinant inbred lines (RILs) from the cross Apo/(2*)Swarna was used to detect quantitative trait loci (QTL) with large effects on grain yield under drought stress using bulk-segregant analysis (BSA). Swarna is an important rainfed lowland rice variety grown on millions of hectares in Asia, but is highly susceptible to drought and aerobic soil conditions. Apo is an aerobic-adapted variety with moderate tolerance to drought. Two rice microsatellite (RM) markers, RM324, and RM416, located on chromosomes 2 and 3, respectively, were shown via BSA to be strongly associated with yield under lowland drought stress. The effects of these QTL were tested in a total of eight hydrological environments over a period of 3 years. The QTL linked to RM416 (DTY(3.1)) had a large effect on grain yield under severe lowland drought stress, explaining about 31% of genetic variance for the trait (P < 0.0001). It also explained considerable variance for yield under mild stress in lowland conditions and aerobic environments. To our knowledge this is the first reported QTL that has a large effect on yield in both lowland drought and aerobic environments. The QTL linked to RM324 (DTY(2.1)) had a highly significant effect on grain yield in lowland drought stress (R(2) = 13-16%) and in two aerobic trials. The effect of these QTL on grain yield was verified to be not mainly due to phenology differences. Effects of DTY(3.1) on yield under stress have been observed in several other rice mapping populations studied at IRRI. Results of this study indicate that BSA is an effective method of identifying QTL alleles with large effects on rice yield under severe drought stress. The Apo alleles for these large-effect QTL for grain yield under drought and aerobic conditions may be immediately exploited in marker-assisted-breeding to improve the drought tolerance of Swarna.

Advances in maize genomics and their value for enhancing genetic gains from breeding

Maize is an important crop for food, feed, forage, and fuel across tropical and temperate areas of the world. Diversity studies at genetic, molecular, and functional levels have revealed that, tropical maize germplasm, landraces, and wild relatives harbor a significantly wider range of genetic variation. Among all types of markers, SNP markers are increasingly the marker-of-choice for all genomics applications in maize breeding. Genetic mapping has been developed through conventional linkage mapping and more recently through linkage disequilibrium-based association analyses. Maize genome sequencing, initially focused on gene-rich regions, now aims for the availability of complete genome sequence. Conventional insertion mutation-based cloning has been complemented recently by EST- and map-based cloning. Transgenics and nutritional genomics are rapidly advancing fields targeting important agronomic traits including pest resistance and grain quality. Substantial advances have been made in methodologies for genomics-assisted breeding, enhancing progress in yield as well as abiotic and biotic stress resistances. Various genomic databases and informatics tools have been developed, among which MaizeGDB is the most developed and widely used by the maize research community. In the future, more emphasis should be given to the development of tools and strategic germplasm resources for more effective molecular breeding of tropical maize products.

Genomic dissection of drought resistance in durum wheat x wild emmer wheat recombinant inbreed line population

Drought is the major factor limiting wheat productivity worldwide. The gene pool of wild emmer wheat, Triticum turgidum ssp. dicoccoides, harbours a rich allelic repertoire for morpho-physiological traits conferring drought resistance. The genetic and physiological bases of drought responses were studied here in a tetraploid wheat population of 152 recombinant inbreed lines (RILs), derived from a cross between durum wheat (cv. Langdon) and wild emmer (acc# G18-16), under contrasting water availabilities. Wide genetic variation was found among RILs for all studied traits. A total of 110 quantitative trait loci (QTLs) were mapped for 11 traits, with LOD score range of 3.0-35.4. Several QTLs showed environmental specificity, accounting for productivity and related traits under water-limited (20 QTLs) or well-watered conditions (15 QTLs), and in terms of drought susceptibility index (22 QTLs). Major genomic regions controlling productivity and related traits were identified on chromosomes 2B, 4A, 5A and 7B. QTLs for productivity were associated with QTLs for drought-adaptive traits, suggesting the involvement of several strategies in wheat adaptation to drought stress. Fifteen pairs of QTLs for the same trait were mapped to seemingly homoeologous positions, reflecting synteny between the A and B genomes. The identified QTLs may facilitate the use of wild alleles for improvement of drought resistance in elite wheat cultivars.

Unraveling the complex trait of crop yield with quantitative trait loci mapping in Brassica napus

Yield is the most important and complex trait for the genetic improvement of crops. Although much research into the genetic basis of yield and yield-associated traits has been reported, in each such experiment the genetic architecture and determinants of yield have remained ambiguous. One of the most intractable problems is the interaction between genes and the environment. We identified 85 quantitative trait loci (QTL) for seed yield along with 785 QTL for eight yield-associated traits, from 10 natural environments and two related populations of rapeseed. A trait-by-trait meta-analysis revealed 401 consensus QTL, of which 82.5% were clustered and integrated into 111 pleiotropic unique QTL by meta-analysis, 47 of which were relevant for seed yield. The complexity of the genetic architecture of yield was demonstrated, illustrating the pleiotropy, synthesis, variability, and plasticity of yield QTL. The idea of estimating indicator QTL for yield QTL and identifying potential candidate genes for yield provides an advance in methodology for complex traits.