Genetic characterization and fine mapping for multi-inflorescence in <Emphasis Type="Italic">Brassica napus</Emphasis> L.

Key message

A major QTL for multi-inflorescence was mapped to a 27.18-kb region on A05 in Brassica napus by integrating QTL mapping, microarray analysis and whole-genome sequencing.

Abstract

Multi-inflorescence is a desirable trait for the genetic improvement of rapeseed (Brassica napus L.). However, the genetic mechanism underlying the multi-inflorescence trait is not well understood. In the present study, a doubled haploid (DH) population derived from a cross between single- and multi-inflorescence lines was investigated for the penetrance of multi-inflorescence across 3 years and genotyped with 257 simple sequence repeat and sequence-related amplified polymorphism loci. A major quantitative trait locus (QTL) for penetrance of multi-inflorescence was mapped to a 9.31-Mb region on chromosome A05, explaining 45.81% of phenotypic variance on average. Subsequently, 13 single-inflorescence and 15 multi-inflorescence DH lines were genotyped with the Brassica microarray, and the QTL interval of multi-inflorescence was narrowed to a 0.74-Mb region with 37 successive single nucleotide polymorphisms between single- and multi-inflorescence groups. A 27.18-kb QTL interval was detected by screening 420 recessive F₂ individuals with genome-specific markers. These results will be valuable for gene cloning and molecular breeding of multi-inflorescence in rapeseed.

     

Identification of candidate genes of QTLs for seed weight in <Emphasis Type="Italic">Brassica napus</Emphasis> through comparative mapping among <Emphasis Type="Italic">Arabidopsis</Emphasis> and <Emphasis Type="Italic">Brassica</Emphasis>species

Background

Map-based cloning of quantitative trait loci (QTLs) in polyploidy crop species remains a challenge due to the complexity of their genome structures. QTLs for seed weight in B. napus have been identified, but information on candidate genes for identified QTLs of this important trait is still rare.

Results

In this study, a whole genome genetic linkage map for B. napus was constructed using simple sequence repeat (SSR) markers that covered a genetic distance of 2,126.4 cM with an average distance of 5.36 cM between markers. A procedure was developed to establish colinearity of SSR loci on B. napus with its two progenitor diploid species B. rapa and B. oleracea through extensive bioinformatics analysis. With the aid of B. rapa and B. oleracea genome sequences, the 421 homologous colinear loci deduced from the SSR loci of B. napus were shown to correspond to 398 homologous loci in Arabidopsis thaliana. Through comparative mapping of Arabidopsis and the three Brassica species, 227 homologous genes for seed size/weight were mapped on the B. napus genetic map, establishing the genetic bases for the important agronomic trait in this amphidiploid species. Furthermore, 12 candidate genes underlying 8 QTLs for seed weight were identified, and a gene-specific marker for BnAP2 was developed through molecular cloning using the seed weight/size gene distribution map in B. napus.

Conclusions

Our study showed that it is feasible to identify candidate genes of QTLs using a SSR-based B. napus genetic map through comparative mapping among Arabidopsis and B. napus and its two progenitor species B. rapa and B. oleracea. Identification of candidate genes for seed weight in amphidiploid B. napus will accelerate the process of isolating the mapped QTLs for this important trait, and this approach may be useful for QTL identification of other traits of agronomic significance.

     

QTL affecting stress response to crowding in a rainbow trout broodstock population

Background

Genomic analyses have the potential to impact selective breeding programs by identifying markers that serve as proxies for traits which are expensive or difficult to measure. Also, identifying genes affecting traits of interest enhances our understanding of their underlying biochemical pathways. To this end we conducted genome scans of seven rainbow trout families from a single broodstock population to identify quantitative trait loci (QTL) having an effect on stress response to crowding as measured by plasma cortisol concentration. Our goal was to estimate the number of major genes having large effects on this trait in our broodstock population through the identification of QTL.

Results

A genome scan including 380 microsatellite markers representing 29 chromosomes resulted in the de novo construction of genetic maps which were in good agreement with the NCCCWA genetic map. Unique sets of QTL were detected for two traits which were defined after observing a low correlation between repeated measurements of plasma cortisol concentration in response to stress. A highly significant QTL was detected in three independent analyses on Omy16, many additional suggestive and significant QTL were also identified. With linkage-based methods of QTL analysis such as half-sib regression interval mapping and a variance component method, we determined that the significant and suggestive QTL explain about 40-43% and 13-27% of the phenotypic trait variation, respectively.

Conclusions

The cortisol response to crowding stress is a complex trait controlled in a sub-sample of our broodstock population by multiple QTL on at least 8 chromosomes. These QTL are largely different from others previously identified for a similar trait, documenting that population specific genetic variants independently affect cortisol response in ways that may result in different impacts on growth. Also, mapping QTL for multiple traits associated with stress response detected trait specific QTL which indicate the significance of the first plasma cortisol measurement in defining the trait. Fine mapping these QTL can lead towards the identification of genes affecting stress response and may influence approaches to selection for this economically important stress response trait.

     

Impact of seed protein alleles from three soybean sources on seed composition and agronomic traits

Key message

Evaluation of seed protein alleles in soybean populations showed that an increase in protein concentration is generally associated with a decrease in oil concentration and yield.

Abstract

Soybean [Glycine max (L.) Merrill] meal is one of the most important plant-based protein sources in the world. Developing cultivars high in seed protein concentration and seed yield is a difficult task because the traits have an inverse relationship. Over two decades ago, a protein quantitative trait loci (QTL) was mapped on chromosome (chr) 20, and this QTL has been mapped to the same position in several studies and given the confirmed QTL designation cqSeed protein-003. In addition, the wp allele on chr 2, which confers pink flower color, has also been associated with increased protein concentration. The objective of our study was to evaluate the effect of cqSeed protein-003 and the wp locus on seed composition and agronomic traits in elite soybean backgrounds adapted to the Midwestern USA. Segregating populations of isogenic lines were developed to test the wp allele and the chr 20 high protein QTL alleles from Danbaekkong (PI619083) and Glycine soja PI468916 at cqSeed protein-003. An increase in protein concentration and decrease in yield were generally coupled with the high protein alleles at cqSeed protein-003 across populations, whereas the effects of wp on protein concentration and yield were variable. These results not only demonstrate the difficulty in developing cultivars with increased protein and yield but also provide information for breeding programs seeking to improve seed composition and agronomic traits simultaneously.

     

Multi-year linkage and association mapping confirm the high number of genomic regions involved in oilseed rape quantitative resistance to blackleg

Key message

A repertoire of the genomic regions involved in quantitative resistance to Leptosphaeria maculans in winter oilseed rape was established from combined linkage-based QTL and genome-wide association (GWA) mapping.

Abstract

Linkage-based mapping of quantitative trait loci (QTL) and genome-wide association studies are complementary approaches for deciphering the genomic architecture of complex agronomical traits. In oilseed rape, quantitative resistance to blackleg disease, caused by L. maculans, is highly polygenic and is greatly influenced by the environment. In this study, we took advantage of multi-year data available on three segregating populations derived from the resistant cv Darmor and multi-year data available on oilseed rape panels to obtain a wide overview of the genomic regions involved in quantitative resistance to this pathogen in oilseed rape. Sixteen QTL regions were common to at least two biparental populations, of which nine were the same as previously detected regions in a multi-parental design derived from different resistant parents. Eight regions were significantly associated with quantitative resistance, of which five on A06, A08, A09, C01 and C04 were located within QTL support intervals. Homoeologous Brassica napus genes were found in eight homoeologous QTL regions, which corresponded to 657 pairs of homoeologous genes. Potential candidate genes underlying this quantitative resistance were identified. Genomic predictions and breeding are also discussed, taking into account the highly polygenic nature of this resistance.

     

Multi-trait and multi-environment QTL analysis reveals the impact of seed colour on seed composition traits in <Emphasis Type="Italic">Brassica napus</Emphasis>

Brassica napus seed composition traits (fibre, protein, oil and fatty acid profiles), seed colour and yield-associated traits are regulated by a complex network of genetic factors. Although previous studies have attempted to dissect the underlying genetic basis for these traits, a more complete picture of the available quantitative trait loci (QTL) variation and any interaction between the different traits is required. In this study, QTL mapping for eleven seed composition traits, seed colour and a yield-related trait (TSW) was conducted in a spring-type canola-quality B. napus doubled haploid (DH) population from a cross between black-seeded (DH12075) and yellow-seeded (YN01-429) lines across five environments. A major QTL associated with fibre traits (acid detergent fibre, acid detergent lignin and neutral detergent fibre) and seed colour (whiteness index) was mapped on chromosome N9 across the five environments. Multi-trait analysis identified QTL which had pleiotropic effect for seed colour and other composition traits. Multi-environment analysis revealed genetic (QTL) × environment effects on most QTL. These findings provide a more detailed insight into the complex QTL networks controlling seed composition and yield-associated traits in canola-quality B. napus.     

Multi-environment QTL analysis of plant and flower morphological traits in tetraploid rose

Key message

Rose morphological traits such as prickles or petal number are influenced by a few key QTL which were detected across different growing environments—necessary for genomics-assisted selection in non-target environments.

Abstract

Rose, one of the world’s most-loved and commercially important ornamental plants, is predominantly tetraploid, possessing four rather than two copies of each chromosome. This condition complicates genetic analysis, and so the majority of previous genetic studies in rose have been performed at the diploid level. However, there may be advantages to performing genetic analyses at the tetraploid level, not least because this is the ploidy level of most breeding germplasm. Here, we apply recently developed methods for quantitative trait loci (QTL) detection in a segregating tetraploid rose population (F₁?=?151) to unravel the genetic control of a number of key morphological traits. These traits were measured both in the Netherlands and Kenya. Since ornamental plant breeding and selection are increasingly being performed at locations other than the production sites, environment-neutral QTL are required to maximise the effectiveness of breeding programmes. We detected a number of robust, multi-environment QTL for such traits as stem and petiole prickles, petal number and stem length that were localised on the recently developed high-density SNP linkage map for rose. Our work explores the complex genetic architecture of these important morphological traits at the tetraploid level, while helping to advance the methods for marker–trait exploration in polyploid species.

     

Novel and major QTL for branch angle detected by using DH population from an exotic introgression in rapeseed (<Emphasis Type="Italic">Brassica napus</Emphasis> L.)

Key message

A high-density SNP map was constructed and several novel QTL for branch angle across six environments in Brassica napus were identified.

Abstract

Branch angle is a major determinant for the ideotype of a plant, while the mechanisms underlying this trait in Brassica napus remain elusive. Herein, we developed one doubled haploid population from a cross involving one Capsella bursa-pastoris derived B. napus intertribal introgression line with the compressed branches and wooden stems, and constructed a high-density SNP map covering the genetic distance of 2242.14 cM, with an average marker interval of 0.73 cM. After phenotypic measurements across six environments, the inclusive composite interval mapping algorithm was conducted to analyze the QTL associated with branch angle. In single-environment analysis, a total of 17 QTL were detected and mainly distributed on chromosomes A01, A03, A09 and C03. Of these, three major QTL, qBA.A03-2, qBA.C03-3 and qBA.C03-4 were steadily expressed, each explaining more than 10% of the phenotypic variation in at least two environments. Compared with other results on rapeseed branch angle, these major QTL were newly detected. In QTL by environment interactions (QEI) mapping, 10 QTL were identified, and the QTL average effect and QEI effect were estimated. Of these, 7 QTL were detected in both single-environment analysis and QEI mapping. Based on the physical positions of SNPs and the functional annotation of the Arabidopsis thaliana genome, 27 genes within the QTL regions were selected as candidate genes, including early auxin-responsive genes, small auxin-up RNA, auxin/indoleacetic acid and gretchenhagen-3. These results may pave the way for deciphering the genetic control of branch angle in B. napus.

     

Quantitative trait loci mapping of heat tolerance in broccoli (<Emphasis Type="Italic">Brassica oleracea</Emphasis> var. <Emphasis Type="Italic">italica</Emphasis>) using genotyping-by-sequencing

Key message

Five quantitative trait loci and one epistatic interaction were associated with heat tolerance in a doubled haploid population of broccoli evaluated in three summer field trials.

Abstract

Predicted rising global temperatures due to climate change have generated a demand for crops that are resistant to yield and quality losses from heat stress. Broccoli (Brassica oleracea var. italica) is a cool weather crop with high temperatures during production decreasing both head quality and yield. Breeding for heat tolerance in broccoli has potential to both expand viable production areas and extend the growing season but breeding efficiency is constrained by limited genetic information. A doubled haploid (DH) broccoli population segregating for heat tolerance was evaluated for head quality in three summer fields in Charleston, SC, USA. Multiple quantitative trait loci (QTL) mapping of 1,423 single nucleotide polymorphisms developed through genotyping-by-sequencing identified five QTL and one positive epistatic interaction that explained 62.1% of variation in heat tolerance. The QTL identified here can be used to develop markers for marker-assisted selection and to increase our understanding of the molecular mechanisms underlying plant response to heat stress.

     

Genetic dissection of seed weight by QTL analysis and detection of allelic variation in Indian and east European gene pool lines of <Emphasis Type="Italic">Brassica juncea</Emphasis>

Key message

Seed weight QTL identified in different populations were synthesized into consensus QTL which were shown to harbor candidate genes by in silico mapping. Allelic variation inferred would be useful in breeding B. juncea lines with high seed weight.

Abstract

Seed weight is an important yield influencing trait in oilseed Brassicas and is a multigenic trait. Among the oilseed Brassicas, Brassica juncea harbors the maximum phenotypic variation wherein thousand seed weight varies from around 2.0 g to more than 7.0 g. In this study, we have undertaken quantitative trait locus/quantitative trait loci (QTL) analysis of seed weight in B. juncea using four bi-parental doubled-haploid populations. These four populations were derived from six lines (three Indian and three east European lines) with parental phenotypic values for thousand seed weight ranging from 2.0 to 7.6 g in different environments. Multi-environment QTL analysis of the four populations identified a total of 65 QTL ranging from 10 to 25 in each population. Meta-analysis of these component QTL of the four populations identified six ‘consensus’ QTL (C-QTL) in A3, A7, A10 and B3 by merging 33 of the 65 component Tsw QTL from different bi-parental populations. Allelic diversity analysis of these six C-QTL showed that Indian lines, Pusajaikisan and Varuna, hold the most positive allele in all the six C-QTL. In silico mapping of candidate genes with the consensus QTL localized 11 genes known to influence seed weight in Arabidopsis thaliana and also showed conserved crucifer blocks harboring seed weight QTL between the A subgenomes of B. juncea and B. rapa. These findings pave the way for a better understanding of the genetics of seed weight in the oilseed crop B. juncea and reveal the scope available for improvement of seed weight through marker-assisted breeding.

     

Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.)

Key message

This report describes an integrative analysis of seed-oil-content quantitative trait loci (QTL) in Brassica napus , using a high-density genetic map to align QTL among different populations.

Abstract

Rapeseed (Brassica napus) is an important source of edible oil and sustainable energy. Given the challenge involved in using only a few genes to substantially increase the oil content of rapeseed without affecting the fatty acid composition, exploitation of a greater number of genetic loci that regulate the oil content variation among rapeseed germplasm is of fundamental importance. In this study, we investigated variation in the seed-oil content among two related genetic populations of Brassica napus, the TN double-haploid population and its derivative reconstructed-F₂ population. Each population was grown in multiple experiments under different environmental conditions. Mapping of quantitative trait loci (QTL) identified 41 QTL in the TN populations. Furthermore, of the 20 pairs of epistatic interaction loci detected, approximately one-third were located within the QTL intervals. The use of common markers on different genetic maps and the TN genetic map as a reference enabled us to project QTL from an additional three genetic populations onto the TN genetic map. In summary, we used the TN genetic map of the B. napus genome to identify 46 distinct QTL regions that control seed-oil content on 16 of the 19 linkage groups of B. napus. Of these, 18 were each detected in multiple populations. The present results are of value for ongoing efforts to breed rapeseed with high oil content, and alignment of the QTL makes an important contribution to the development of an integrative system for genetic studies of rapeseed.     

Genome-wide association mapping and agronomic impact of cowpea root architecture

Key message

Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance.

Abstract

Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.

     

Bimodality of stable and plastic traits in plants

Key message

We discovered an unexpected mode of bimodal distribution of stable and plastic traits, which was consistent for homologous traits of 32 varieties of seven species both in well-irrigated fields and dry conditions.

Abstract

We challenged archived genetic mapping data for 36 fruit, seed, flower and yield traits in tomato and found an unexpected bimodal distribution in one measure of trait variability, the mean coefficient of variation, with some traits being consistently more variable than others. To determine the degree of conservation of this distribution among higher plants, we compared 18 homologous phenotypes, including yield and seed production, across different crop species grown in a common ‘crop garden’ experiment. The set included 32 varieties of tomato, eggplant, pepper, melon, watermelon, sunflower and maize. Estimates of canalization were obtained using a ‘canalization replication’ experimental design that generated multiple estimates of the coefficient of variation of traits, as well as their reaction norms in optimal and water-stressed field plots. A common pattern of bimodal distribution of stable and plastic traits was observed for all the varieties and for a wild weed (Solanum nigrum). We propose that canalization profiles of traits in a variety of taxa were ancestrally selected to maximize adaptation and reproductive success.

     

Quantitative trait loci for seed yield and yield-related traits, and their responses to reduced phosphorus supply in Brassica napus

Background and Aims

One of the key targets of breeding programmes in rapeseed (Brassica napus) is to develop high-yield varieties. However, the lack of available phosphorus (P) in soils seriously limits rapeseed production. The aim of this study was to dissect the genetic control of seed yield and yield-related traits in B. napus grown with contrasting P supplies.

Methods

Two-year field trials were conducted at one site with normal and low P treatments using a population of 124 recombinant inbred lines derived from a cross between ‘B104-2’ and ‘Eyou Changjia’. Seed yield, seed weight, seed number, pod number, plant height, branch number and P efficiency coefficient (PEC) were investigated. Quantitative trait locus (QTL) analysis was performed by composite interval mapping.

Key Results

The phenotypic values of most of the tested traits were reduced under the low P conditions. In total, 74 putative QTLs were identified, contributing 7·3–25·4 % of the phenotypic variation. Of these QTLs, 16 (21·6 %) were detected in two seasons and in the mean value of two seasons, and eight QTLs for two traits were conserved across P levels. Low-P-specific QTLs were clustered on chromosomes A1, A6 and A8. By comparative mapping between Arabidopsis and B. napus, 161 orthologues of 146 genes involved in Arabidopsis P homeostasis and/or yield-related trait control were associated with 45 QTLs corresponding to 23 chromosomal regions. Four gene-based markers developed from genes involved in Arabidopsis P homeostasis were mapped to QTL intervals.

Conclusions

Different genetic determinants were involved in controlling seed yield and yield-related traits in B. napus under normal and low P conditions. The QTLs detected under reduced P supply may provide useful information for improving the seed yield of B. napus in soils with low P availability in marker-assisted selection.     

Identification and validation of QTL and their associated genes for pre-emergent metribuzin tolerance in hexaploid wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Background

Herbicide tolerance is an important trait that allows effective weed management in wheat crops. Genetic knowledge of metribuzin tolerance in wheat is needed to develop new cultivars for the industry. Here, we evaluated metribuzin tolerance in a recombinant inbred line (RIL) mapping population derived from Synthetic W7984 and Opata 85 over two consecutive years to identify quantitative trait loci (QTL) contributing to the trait. Herbicide tolerance was measured by two chlorophyll traits, SPAD chlorophyll content index (CCI) and visual senescence score (SNS). The markers associated with major QTL from Synthetic W7984, positively contributing to reduced phytotoxic effects under herbicide treatment were validated in two F_3/4 recombinant inbred populations developed from crosses of Synthetic W7984?×?Westonia and Synthetic W7984?×?Lang.

Results

Composite interval mapping (CIM) identified four QTL, two on chromosome 4A and one each on chromosomes 2D and 1A. The chromosomal position of the two QTL mapped on 4A within 10 cM intervals was refined and validated by multiple interval mapping (MIM). The major QTL affecting both measures of tolerance jointly explained 42 and 45% of the phenotypic variation by percentage CCI reduction and SNS, respectively. The identified QTL have a pure additive effect. The metribuzin tolerant allele of markers, Xgwm33 and Xbarc343, conferred lower phytotoxicity and explained the maximum phenotypic variation of 28.8 and 24.5%, respectively. The approximate physical localization of the QTL revealed the presence of five candidate genes (ribulose-bisphosphate carboxylase, oxidoreductase (rbcS), glycosyltransferase, serine/threonine-specific protein kinase and phosphotransferase) with a direct role in photosynthesis and/or metabolic detoxification pathways.

Conclusion

Metribuzin causes photo-inhibition by interrupting electron flow in PSII. Consequently, chlorophyll traits enabled the measure of high proportion of genetic variability in the mapping population. The validated molecular markers associated with metribuzin tolerance mediating QTL may be used in marker-assisted breeding to select metribuzin tolerant lines. Alternatively, validated favourable alleles could be introgressed into elite wheat cultivars to enhance metribuzin tolerance and improve grain yield in dryland farming for sustainable wheat production.

     

Metabolomic analysis of tomato seed germination

Introduction

Seed germination is inherently related to seed metabolism, which changes throughout its maturation, desiccation and germination processes. The metabolite content of a seed and its ability to germinate are determined by underlying genetic architecture and environmental effects during development.

Objective

This study aimed to assess an integrative approach to explore genetics modulating seed metabolism in different developmental stages and the link between seed metabolic- and germination traits.

Methods

We have utilized gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) metabolite profiling to characterize tomato seeds during dry and imbibed stages. We describe, for the first time in tomato, the use of a so-called generalized genetical genomics (GGG) model to study the interaction between genetics, environment and seed metabolism using 100 tomato recombinant inbred lines (RILs) derived from a cross between Solanum lycopersicum and Solanum pimpinellifolium.

Results

QTLs were found for over two-thirds of the metabolites within several QTL hotspots. The transition from dry to 6 h imbibed seeds was associated with programmed metabolic switches. Significant correlations varied among individual metabolites and the obtained clusters were significantly enriched for metabolites involved in specific biochemical pathways.

Conclusions

Extensive genetic variation in metabolite abundance was uncovered. Numerous identified genetic regions that coordinate groups of metabolites were detected and these will contain plausible candidate genes. The combined analysis of germination phenotypes and metabolite profiles provides a strong indication for the hypothesis that metabolic composition is related to germination phenotypes and thus to seed performance.

     

A QTL located on chromosome 3D enhances the selenium concentration of wheat grain by improving phytoavailability and root structure

Background and aims

As an essential mineral element, selenium (Se) plays a critical role in human health. Given the low concentrations (<100 mg Se kg–1) of Se in staple crops, the identification of genetic resources with enriched Se, as well as the genes controlling Se concentration, is valuable for the marker-assisted selection of Se-rich varieties.

Methods

We determined the chromosomal quantitative trait (QTL) for Se concentration over two consecutive plant growth cycles using recombinant inbred lines (RILs) treated with two different concentrations of Se under both field-grown and hydroponic conditions.

Results

Several QTL for Se concentration were detected across the different treatments. Significant genotypic variation in the tissues of the RIL was found at Se-deficicencycondition. Notably, a QTL located on 3D (interval 214.00–218.00, Qse.sau-3D) affected root length and Se concentration in the leaves and grains, suggesting the existence of the same allele with distinctly different functions. However, the QTL for the agronomic traits measured (plant height, flowering time, and tillering number) and Se concentration were not found to be located on the same chromosomal regions, suggesting that marker-assisted selection for both traits is feasible. Se concentrations in the grains were primarily determined by the mineral transport efficiency of the lines, and the line with the highest Se concentration in the grains always possessed larger, more fibrous root systems. The concentrations of Se in the plant tissues were in the order of: root > stem > grain.

Conclusions

This is the first study to document a Se-rich synthetic wheat line, and root structure and Se grain concentration was strongly affected by QTL located on 3D.

     

Modelling the genetic architecture of flowering time control in barley through nested association mapping

Background

Barley, globally the fourth most important cereal, provides food and beverages for humans and feed for animal husbandry. Maximizing grain yield under varying climate conditions largely depends on the optimal timing of flowering. Therefore, regulation of flowering time is of extraordinary importance to meet future food and feed demands. We developed the first barley nested association mapping (NAM) population, HEB-25, by crossing 25 wild barleys with one elite barley cultivar, and used it to dissect the genetic architecture of flowering time.

Results

Upon cultivation of 1,420 lines in multi-field trials and applying a genome-wide association study, eight major quantitative trait loci (QTL) were identified as main determinants to control flowering time in barley. These QTL accounted for 64% of the cross-validated proportion of explained genotypic variance (p_G). The strongest single QTL effect corresponded to the known photoperiod response gene Ppd-H1. After sequencing the causative part of Ppd-H1, we differentiated twelve haplotypes in HEB-25, whereof the strongest exotic haplotype accelerated flowering time by 11 days compared to the elite barley haplotype. Applying a whole genome prediction model including main effects and epistatic interactions allowed predicting flowering time with an unmatched accuracy of 77% of cross-validated p_G.

Conclusions

The elaborated causal models represent a fundamental step to explain flowering time in barley. In addition, our study confirms that the exotic biodiversity present in HEB-25 is a valuable toolbox to dissect the genetic architecture of important agronomic traits and to replenish the elite barley breeding pool with favorable, trait-improving exotic alleles.