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GK-G, PR, JT contributed equally to experimental design, data analysis andinterpretation/writing of manuscript;, RP, MH, KF, RA genome analyses andinterpretation; ZF, AK data analysis and physical map construction; EH, CC, JTMAGIC map construction; MA rice-wheat phylogenomic; AS, DK, mate-pairlibraries; PS. BD, FC, PL, Chinese Spring x Renan molecular genetic map andannotation of genome sequence; NW-H, UB, PE, DF, AJ analysis of genespace and QTL, SB, M-AN, development of Bionano alignments and tools; JD,HŠ, JŠ, HT, flow sorting of chromosomes, BAC library construction andBionano maps; M-CL fingerprinting of BAC library; FC, MP gene annotation;DC, ZR, AK58 genome assembly, JN-P, genome assembly; DI in-housesoftware development; IWGSC, genome assembly network, D-HK, CENH3antibody cytology; RA, planning of experiments and writing of manuscript.All authors have read and approved the final manuscript.; Background: Numerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome.Results: Using chromosome 7A of wheat as a model, sequence-finished megabase-scale sections of this chromosome were established by combining a new independent assembly using a bacterial artificial chromosome (BAC)-based physical map, BAC pool paired-end sequencing, chromosome-arm-specific mate-pair sequencing and Bionano optical mapping with the International Wheat Genome Sequencing Consortium RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region.Conclusions: Sufficient genome sequence information is shown to now be available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and that yield attributes are affected by five F-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.

The flowers of major cereals are arranged on reproductive branches known as spikelets, which group together to form an inflorescence. Diversity for inflorescence architecture has been exploited during domestication to increase crop yields, and genetic variation for this trait has potential to further boost grain production. Multiple genes that regulate inflorescence architecture have been identified by studying alleles that modify gene activity or dosage; however, little is known in wheat. Here, we show TEOSINTE BRANCHED1 (TB1) regulates inflorescence architecture in bread wheat (Triticum aestivum) by investigating lines that display a form of inflorescence branching known as "paired spikelets." We show that TB1 interacts with FLOWERING LOCUS T1 and that increased dosage of TB1 alters inflorescence architecture and growth rate in a process that includes reduced expression of meristem identity genes, with allelic diversity for TB1 found to associate genetically with paired spikelet development in modern cultivars. We propose TB1 coordinates formation of axillary spikelets during the vegetative to floral transition and that alleles known to modify dosage or function of TB1 could help increase wheat yields.

Background The proportion of granule types in wheat starch is an important characteristic that can affect its functionality. It is widely accepted that granule types are either large, disc-shaped A-type granules or small, spherical B-type granules. Additionally, there are some reports of the tiny C-type granules. The differences between these granule types are due to its carbohydrate composition and crystallinity which is highly, but not perfectly, correlated with the granule size. A majority of the studies that have considered granule types analyse them based on a size threshold rather than chemical composition. This is understandable due to the expense of separating starch into different types. While the use of a size threshold to classify granule type is a low-cost measure, this results in misclassification. We present an alternative, statistical method to quantify the proportion of granule types by a fit of the mixture distribution, along with an R package, a web based app and a video tutorial for how to use the web app to enable its straightforward application. Results Our results show that the reliability of the genotypic effects increase approximately 60% using the proportions of the A-type and B-type granule estimated by the mixture distribution over the standard size-threshold measure. Although there was a marginal drop in reliability for C-type granules. The latter is likely due to the low observed genetic variance for C-type granules. Conclusions The determination of the proportion of granule types from size-distribution is better achieved by using the mixing probabilities from the fit of the mixture distribution rather than using a size-threshold. Electronic supplementary material The online version of this article (10.1186/s13007-017-0259-2) contains supplementary material, which is available to authorized users.

Cereal grains are the major source of fructan intake with potential health benefits for human. Measurement of fructan levels in cereal breeding populations is a great challenge and time-consuming. In this study, K-FRUCHK and K-FRUC kits commercialized by Megazyme International Limited (Bray, Ireland) were modified and optimized in a 96 deep well plate and a thermal block (BioShake iQ, Q.Instruments, Jena, Germany). The modified assays are able to measure up to 91 samples per day with a range of fructan concentrations (0.4–10.8% in this experiment). Of the two assays, the modified K-FRUC assay is more desirable for measuring fructan levels in cereal grains with high starch content. This assay was successfully used to screen three wheat starch synthase IIa (SSIIa) mutation populations with a total of 466 lines. All 21 SSIIa triple null mutants showed high fructan levels (3.1–10.8%) in wholemeal flours; while all single and double nulls were similar to wild types with ∼1% of fructans. This result indicates that lack of entire SSIIa activity changes carbon flux from starch synthesis into fructan pathway. The identified 21 triple null wheat lines may have potential use for the production of high fructan staple foods.

BackgroundIdentifying the genetic architecture of complex traits requires access to populations with sufficient genetic diversity and recombination. Multi-parent Advanced Generation InterCross (MAGIC) populations are a powerful resource due to their balanced population structure, allelic diversity and enhanced recombination. However, implementing a MAGIC population in complex polyploids such as wheat is not trivial, as wheat harbours many introgressions, inversions and other genetic factors that interfere with linkage mapping.ResultsBy utilising a comprehensive crossing strategy, additional rounds of mixing and novel genotype calling approaches, we developed a bread wheat eight parent MAGIC population made up of more than 3000 fully genotyped recombinant inbred lines derived from 2151 distinct crosses, and achieved a dense genetic map covering the complete genome. Further rounds of inter-crossing led to increased recombination in inbred lines, as expected. The comprehensive and novel approaches taken in the development and analysis of this population provide a platform for genetic discovery in bread wheat. We identify previously unreported structural variation highlighted by segregation distortion, along with the identification of epistatic allelic interactions between specific founders. We demonstrate the ability to conduct high resolution QTL mapping using the number of recombination events as a trait, and identify several significant QTLs explaining greater than 50% of the variance.ConclusionsWe report on a novel and effective resource for genomic and trait exploration in hexaploid wheat, that can be used to detect small genetic effects and epistatic interactions due to the high level of recombination and large number of lines. The interactions and genetic effects identified provide a basis for ongoing research to understand the basis of allelic frequencies across the genome, particularly where economically important loci are involved.

In wheat (Triticum aestivum L.) canopy architecture influences light penetration into the canopy and radiation use efficiency particularly during the period between stem elongation and anthesis which is the critical time for the determination of yield. Despite large differences in canopy architecture among spring wheat genotypes, ranging from erectophile to planophile upper leaves, there is little prior evidence to suggest that selection for canopy architecture influences yield. In this study we evaluated the variation for canopy architecture in a 4-way MAGIC population (n=∼ 1000 lines) developed from 4 Australian commercial spring wheats and an 8-way MAGIC population (n=∼ 300 lines) developed from 3 Australian and 5 northern hemisphere commercial wheats. The 4-way population was grown at both an irrigated and a dryland site in southern New South Wales whereas the 8-way population was grown at the irrigated site. We also measured grain yield, plant height and crop development stage at the irrigated site. Using a smaller subset of lines which we grouped into either erectophile or planophile we studied how canopy architecture influences grain yield and associated yield traits (above-ground biomass (AGBM), harvest index, yield components, flowering time and height). The grain yield in the latter experiments varied from 5 to 6 t ha−1. Averaged over two years and two sowing dates in each year lines that were erectophile yielded 13% more than the planophile lines and most of this yield advantage was associated with a higher AGBM (11%). Erectophile lines had 24% more grains per unit area but a 9% lower grain weight. Erectophile lines flowered 2 days later than planophile lines and they were 7 cm shorter. Lodging, although rare in these studies, was more evident in the planophile lines. In both MAGIC populations the most erectophile lines yielded 24% more grain than the most planophile lines. Mapping was conducted on the 1000 lines from the 4-way MAGIC population grown at the irrigated and the dryland site. It showed that genetic control of canopy architecture was complex but QTL were generally repeatable at both sites. Significant QTL were identified on most chromosomes. G x E was low for canopy architecture as the scores were repeatable across years (r2 = 0.85). This trait opens the way to improve wheat yields via increasing crop biomass which in the past has been largely intractable in breeding programs.

Highlight Rhizosheath size of wheat was used as a surrogate for root hair length to map QTL in lines derived from multiparent advanced generation intercrosses., Rhizosheaths comprise soil that adheres to plant roots and, in some species, are indicative of root hair length. In this study, the genetics of rhizosheath size in wheat was investigated by screening the progeny of multiparent advanced generation intercrosses (MAGIC). Two MAGIC populations were screened for rhizosheath size using a high throughput method. One MAGIC population was developed from intercrosses between four parents (4-way) and the other from intercrosses between eight parents (8-way). Transgressive segregation for rhizosheath size was observed in both the 4-way and 8-way MAGIC populations. A quantitative trait loci (QTL) analysis of the 4-way population identified six major loci located on chromosomes 2B, 4D, 5A, 5B, 6A, and 7A together accounting for 42% of the variation in rhizosheath size. Rhizosheath size was strongly correlated with root hair length and was robust across different soil types in the absence of chemical constraints. Rhizosheath size in the MAGIC populations was a reliable surrogate for root hair length and, therefore, the QTL identified probably control root hair elongation. Members of the basic helix-loop-helix family of transcription factors have previously been identified to regulate root hair length in Arabidopsis and rice. Since several wheat members of the basic helix-loop-helix family of genes are located within or near the QTL, these genes are candidates for controlling the long root hair trait. The QTL for rhizosheath size identified in this study provides the opportunity to implement marker-assisted selection to increase root hair length for improved phosphate acquisition in wheat.

MAGIC populations present novel challenges and opportunities in crops due to their complex pedigree structure. They offer great potential both for dissecting genomic structure and for improving breeding populations. The past decade has seen the rise of multiparental populations as a study design offering great advantages for genetic studies in plants. The genetic diversity of multiple parents, recombined over several generations, generates a genetic resource population with large phenotypic diversity suitable for high-resolution trait mapping. While there are many variations on the general design, this review focuses on populations where the parents have all been inter-mated, typically termed Multi-parent Advanced Generation Intercrosses (MAGIC). Such populations have already been created in model animals and plants, and are emerging in many crop species. However, there has been little consideration of the full range of factors which create novel challenges for design and analysis in these populations. We will present brief descriptions of large MAGIC crop studies currently in progress to motivate discussion of population construction, efficient experimental design, and genetic analysis in these populations. In addition, we will highlight some recent achievements and discuss the opportunities and advantages to exploit the unique structure of these resources post-QTL analysis for gene discovery.

We present new association mapping methods which address the unique challenges of analyzing genome-wide data from multi-environment plant studies. Association studies on a genome-wide scale are being performed in plants. Unlike human studies, plant studies contain replicates whose data may be recorded across different environments. Plant studies also often employ elaborate experimental designs for controlling extraneous phenotypic variation. As a result, the genome-wide analysis of data from plant studies can be challenging. In this paper, we present QK-based association mapping for the analysis of data from plant association studies. In doing so, we have developed: (a) a general multivariate QK framework for association mapping in plant studies of arbitrary complexity; (b) a new weighted two-stage analysis approach for QK-based association mapping; (c) a heuristic procedure for determining when two-stage analysis is appropriate; and (d) a Monte Carlo sampling procedure for controlling the genome-wide type I error rate. We conduct a simulation study to evaluate the performance of our genome-wide mapping technique. We also analyze data from a multi-environment association study in wheat.

Summary Resistant starch (RS), a type of dietary fibre, plays an important role in human health; however, the content of RS in most modern processed starchy foods is low. Cereal starch, when structurally manipulated through a modified starch biosynthetic pathway to greatly increase the amylose content, could be an important food source of RS. Transgenic studies have previously revealed the requirement of simultaneous down-regulation of two starch branching enzyme (SBE) II isoforms both located on the long arm of chromosome 2, namely SBEIIa and SBEIIb, to elevate the amylose content in wheat from ~25% to ~75%. The current study revealed close proximity of genes encoding SBEIIa and SBEIIb isoforms in wheat with a genetic distance of 0.5 cM on chromosome 2B. A series of deletion and single nucleotide polymorphism (SNP) loss of function alleles in SBEIIa, SBEIIb or both was isolated from two different wheat populations. A breeding strategy to combine deletions and SNPs generated wheat genotypes with altered expression levels of SBEIIa and SBEIIb, elevating the amylose content to an unprecedented ~85%, with a marked concomitant increase in RS content. Biochemical assays were used to confirm the complete absence in the grain of expression of SBEIIa from all three genomes in combination with the absence of SBEIIb from one of the genomes.

Multiparent Advanced Generation Inter-Cross (MAGIC) populations are now being utilized to more accurately identify the underlying genetic basis of quantitative traits through quantitative trait loci (QTL) analyses and subsequent gene discovery. The expanded genetic diversity present in such populations and the amplified number of recombination events mean that QTL can be identified at a higher resolution. Most QTL analyses are conducted separately for each trait within a single environment. Separate analysis does not take advantage of the underlying correlation structure found in multienvironment or multitrait data. By using this information in a joint analysis—be it multienvironment or multitrait — it is possible to gain a greater understanding of genotype- or QTL-by-environment interactions or of pleiotropic effects across traits. Furthermore, this can result in improvements in accuracy for a range of traits or in a specific target environment and can influence selection decisions. Data derived from MAGIC populations allow for founder probabilities of all founder alleles to be calculated for each individual within the population. This presents an additional layer of complexity and information that can be utilized to identify QTL. A whole-genome approach is proposed for multienvironment and multitrait QTL analysis in MAGIC. The whole-genome approach simultaneously incorporates all founder probabilities at each marker for all individuals in the analysis, rather than using a genome scan. A dimension reduction technique is implemented, which allows for high-dimensional genetic data. For each QTL identified, sizes of effects for each founder allele, the percentage of genetic variance explained, and a score to reflect the strength of the QTL are found. The approach was demonstrated to perform well in a small simulation study and for two experiments, using a wheat MAGIC population.

SUMMARYThe present paper provides an approach for the design and analysis of variety trials that are used to obtain quality trait data. These trials are multi-phase in nature, comprising a field phase followed by one or more laboratory phases. Typically the laboratory phases are costly relative to the field phase and this imposes a limit on the number of samples that can be tested. Historically, this has been achieved by sacrificing field replication, either by testing a single replicate plot for each variety or a single composite sample, obtained by combining material from several field replicates. An efficient statistical analysis cannot be applied to such data so that valid inference and accurate prediction of genetic effects may be precluded. A solution that has appeared recently in the literature is the use of partial replication, in which some varieties are tested using multiple field replicates and the remainder as single replicates only. In the present paper, an approach is proposed in which some varieties are tested using individual field replicate samples and others as composite samples. Replication in the laboratory is achieved by splitting a relatively small number of field samples into sub-samples for separate processing. It is shown that, if necessary, some of the composite samples may be split for this purpose. It is also shown that, given a choice of field compositing and laboratory replication strategy, an efficient design for a laboratory phase may be obtained using model-based techniques. The methods are illustrated using two examples. It is demonstrated that the approach provides more accurate variety predictions compared with the partial replication approach and that the gains can be substantial if the field variation is large relative to the laboratory variation.

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat. © 2014 The Authors Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Summary The pursuits of white features and white fleeces free of pigmented fibre have been important selection objectives for many sheep breeds. The cause and inheritance of non-white colour patterns in sheep has been studied since the early 19th century. Discovery of genetic causes, especially those which predispose pigmentation in white sheep, may lead to more accurate selection tools for improved apparel wool. This article describes an extended QTL study for 13 skin and fibre pigmentation traits in sheep. A total of 19 highly significant, 10 significant and seven suggestive QTL were identified in a QTL mapping experiment using an Awassi × Merino × Merino backcross sheep population. All QTL on chromosome 2 exceeded a LOD score of greater than 4 (range 4.4–30.1), giving very strong support for a major gene for pigmentation on this chromosome. Evidence of epistatic interactions was found for QTL for four traits on chromosomes 2 and 19. The ovine TYRP1 gene on OAR 2 was sequenced as a strong positional candidate gene. A highly significant association (P

The relationships between starch structure and functionality are important in underpinning the industrial and nutritional utilisation of starches. In this work, the relationships between the biosynthesis, structure, molecular organisation and functionality have been examined using a series of defined genotypes in barley with low (20%), standard (20-30%), elevated (30-50%) and high (50%) amylose starches. A range of techniques have been employed to determine starch physical features, higher order structure and functionality. The two genetic mechanisms for generating high amylose contents (down-regulation of branching enzymes and starch synthases, respectively) yielded starches with very different amylopectin structures but similar gelatinisation and viscosity properties driven by reduced granular order and increased amylose content. Principal components analysis (PCA) was used to elucidate the relationships between genotypes and starch molecular structure and functionality. Parameters associated with granule order (PC1) accounted for a large percentage of the variance (57%) and were closely related to amylose content. Parameters associated with amylopectin fine structure accounted for 18% of the variance but were less closely aligned to functionality parameters.

The large and complex genome of wheat makes genetic and genomic analysis in this important species both expensive and resource intensive. The application of next-generation sequencing technologies is particularly resource intensive, with at least 17 Gbp of sequence data required to obtain minimal (1×) coverage of the genome. A similar volume of data would represent almost 40× coverage of the rice genome. Progress can be made through the establishment of consortia to produce shared genomic resources. Australian wheat genome researchers, working with Bioplatforms Australia, have collaborated in a national initiative to establish a genetic diversity dataset representing Australian wheat germplasm based on whole genome next-generation sequencing data. Here, we describe the establishment and validation of this resource which can provide a model for broader international initiatives for the analysis of large and complex genomes.

A novel mechanism for increasing vegetative biomass and grain yield has been identified in wheat (Triticum aestivum). RNAi-mediated down-regulation of Glucan, Water-Dikinase (GWD), the primary enzyme required for starch phosphorylation, under the control of an endosperm-specific promoter, resulted in a decrease in starch phosphate content and an increase in grain size. Unexpectedly, consistent increases in vegetative biomass and grain yield were observed in subsequent generations. In lines where GWD expression was decreased, germination rate was slightly reduced. However, significant increases in vegetative growth from the two leaf stage were observed. In glasshouse pot trials, down-regulation of GWD led to a 29% increase in grain yield while in glasshouse tub trials simulating field row spacing and canopy development, GWD down-regulation resulted in a grain yield increase of 26%. The enhanced yield resulted from a combination of increases in seed weight, tiller number, spikelets per head and seed number per spike. In field trials, all vegetative phenotypes were reproduced with the exception of increased tiller number. The expression of the transgene and suppression of endogenous GWD RNA levels were demonstrated to be grain specific. In addition to the direct effects of GWD down-regulation, an increased level of α-amylase activity was present in the aleurone layer during grain maturation. These findings provide a potentially important novel mechanism to increase biomass and grain yield in crop improvement programmes.

We present the first results from a novel multiparent advanced generation inter-cross (MAGIC) population derived from four elite wheat cultivars. The large size of this MAGIC population (1579 progeny), its diverse genetic composition and high levels of recombination all contribute to its value as a genetic resource. Applications of this resource include interrogation of the wheat genome and the analysis of gene-trait association in agronomically important wheat phenotypes. Here, we report the utilization of a MAGIC population for the first time for linkage map construction. We have constructed a linkage map with 1162 DArT, single nucleotide polymorphism and simple sequence repeat markers distributed across all 21 chromosomes. We benchmark this map against a high-density DArT consensus map created by integrating more than 100 biparental populations. The linkage map forms the basis for further exploration of the genetic architecture within the population, including characterization of linkage disequilibrium, founder contribution and inclusion of an alien introgression into the genetic map. Finally, we demonstrate the application of the resource for quantitative trait loci mapping using the complex traits plant height and hectolitre weight as a proof of principle. © 2012 CSIRO. Plant Biotechnology Journal

For many years, genetic markers have been the building blocks in assembling genomic knowledge. Improved technology and methods for collecting marker data have increased accuracy, increased throughput, and reduced cost. However, common genotyping technology still produces far fewer markers in plant species than in animals and humans. We propose a new type of genetic marker based on the Diversity Arrays Technology (DArT) genotyping system for organisms lacking a reference genetic sequence. These markers are based directly on microarray probe intensity profiles and hence are called iDArTs. They require no additional genotyping beyond screening with a DArT array. Since standard methods of genetic analysis cannot be used with these continuous markers, we develop novel methods for the common bi-parental experimental designs doubled haploids, recombinant inbred lines, and backcrosses. These enable the augmentation of genetic maps with iDArTs and permit quantitative trait locus mapping with both discrete and continuous markers. We use simulation to demonstrate the power of this approach for marker mapping. In addition, we construct maps and perform linkage analysis for these DArT genotypes using the doubled haploid progeny lines from a cross between the wheat cultivars Chara and Glenlea. These methods allow access to a previously untapped genetic resource by extracting additional information from the raw data. With no additional genotyping cost, we are able to double the number of markers mapped and thereby increase genome coverage.

The genetic and phenotypic relationships among wheat quality predictors and sponge and dough bread making were evaluated in a population derived from a cross between an Australian cultivar 'Chara' and a Canadian cultivar 'Glenlea'. The genetic correlation across sites for sponge and dough loaf volume was high; however, phenotypic correlations across sites for loaf volume were relatively low compared with rheological tests. The large difference between sites was most likely due to temperature differences during grain development reflected in a decrease in the percentage of unextractable polymeric protein and mixing time. Predictive tests (mixograph, extensograph, protein content and composition, micro-zeleny and flour viscosity) showed inconsistent and generally poor correlations with end-product performance (baking volume and slice area) at both sites, with no single parameter being effective as a predictor of end-product performance. The difference in the relationships between genetic and phenotypic correlations highlights the requirement to develop alternative methods of selection for breeders and bakers in order to maximise both genetic gain and predictive assessment of grain quality.

Endosperm carotenoid content in wheat is a primary determinant of flour colour and this affects both the nutritional value of the grain and its utility for different applications. Utilising wheat rice synteny two genes, epsilon-cyclase (epsilon-LCY) and phytoene synthase (Psy-A1), were identified as candidate genes for two of the QTL affecting lutein content in wheat endosperm. Analysis of the sequence changes in epsilon-LCY and Psy-A1 revealed possible causal mechanisms for both QTL. A point mutation in epsilon-LCY results in the substitution of a conserved amino acid in the high lutein allele. This substitution has been observed in high lutein-accumulating species from the Gentiales order. In Psy-A1, a sequence duplication at the end of exon 2 creates a new splice site and causes alternative splicing of the transcript and activation of a cryptic exon, resulting in four different transcripts: a wild-type transcript, two transcripts with early terminations and a transcript that would produce an in-frame, albeit longer protein. Only the wild-type splice variant produced an enzymatically active protein and its mRNA abundance was reduced by titration with the other splice variants. This reduction in wild-type mRNA is argued to result in a reduction in PSY protein and thus carotenoid content in wheat.

Wheat starch is considered to have a low paste viscosity relative to other starches. Consequently, wheat starch is not preferred for many applications as compared to other high paste viscosity starches. Increasing the viscosity of wheat starch is expected to increase the functionality of a range of wheat flour-based products in which the texture is an important aspect of consumer acceptance (e.g., pasta, and instant and yellow alkaline noodles). To understand the molecular basis of starch viscosity, we have undertaken a comprehensive structural and rheological analysis of starches from a genetically diverse set of wheat genotypes, which revealed significant variation in starch traits including starch granule protein content, starch-associated lipid content and composition, phosphate content, and the structures of the amylose and amylopectin fractions. Statistical analysis highlighted the association between amylopectin chains of 18-25 glucose residues and starch pasting properties. Principal component analysis also identified an association between monoesterified phosphate and starch pasting properties in wheat despite the low starch-phosphate level in wheat as compared to tuber starches. We also found a strong negative correlation between the phosphate ester content and the starch content in flour. Previously observed associations between internal starch granule fatty acids and the swelling peak time and pasting temperature have been confirmed. This study has highlighted a range of parameters associated with increased starch viscosity that could be used in prebreeding/breeding programs to modify wheat starch pasting properties.

Background Next-generation sequencing technologies provide new opportunities to identify the genetic components responsible for trait variation. However, in species with large polyploid genomes, such as bread wheat, the ability to rapidly identify genes underlying quantitative trait loci (QTL) remains non-trivial. To overcome this, we introduce a novel pipeline that analyses, by RNA-sequencing, multiple near-isogenic lines segregating for a targeted QTL. Results We use this approach to characterize a major and widely utilized seed dormancy QTL located on chromosome 4AL. It exploits the power and mapping resolution afforded by large multi-parent mapping populations, whilst reducing complexity by using multi-allelic contrasts at the targeted QTL region. Our approach identifies two adjacent candidate genes within the QTL region belonging to the ABA-induced Wheat Plasma Membrane 19 family. One of them, PM19-A1, is highly expressed during grain maturation in dormant genotypes. The second, PM19-A2, shows changes in sequence causing several amino acid alterations between dormant and non-dormant genotypes. We confirm that PM19 genes are positive regulators of seed dormancy. Conclusions The efficient identification of these strong candidates demonstrates the utility of our transcriptomic pipeline for rapid QTL to gene mapping. By using this approach we are able to provide a comprehensive genetic analysis of the major source of grain dormancy in wheat. Further analysis across a diverse panel of bread and durum wheats indicates that this important dormancy QTL predates hexaploid wheat. The use of these genes by wheat breeders could assist in the elimination of pre-harvest sprouting in wheat. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0665-6) contains supplementary material, which is available to authorized users.

The domestication of cereal crops such as wheat, maize, rice and barley has included the modification of inflorescence architecture to improve grain yield and ease harvesting(1). Yield increases have often been achieved through modifying the number and arrangement of spikelets, which are specialized reproductive branches that form part of the inflorescence. Multiple genes that control spikelet development have been identified in maize, rice and barley(2-5). However, little is known about the genetic underpinnings of this process in wheat. Here, we describe a modified spikelet arrangement in wheat, termed paired spikelets. Combining comprehensive QTL and mutant analyses, we show that Photoperiod-1 (Ppd-1), a pseudo-response regulator gene that controls photoperiod-dependent floral induction, has a major inhibitory effect on paired spikelet formation by regulating the expression of FLOWERING LOCUS T (FT)(6,7). These findings show that modulated expression of the two important flowering genes, Ppd-1 and FT, can be used to form a wheat inflorescence with a more elaborate arrangement and increased number of grain producing spikelets.

International audience; Fusarium pathogens cause two major diseases in cereals, Fusarium crown rot (FCR) and head blight (FHB). A large-effect locus conferring resistance to FCR disease was previously located to chromosome arm 3BL (designated as Qcrs-3B) and several independent sets of near isogenic lines (NILs) have been developed for this locus. In this study, five sets of the NILs were used to examine transcriptional changes associated with the Qcrs-3B locus and to identify genes linked to the resistance locus as a step towards the isolation of the causative gene(s). Of the differentially expressed genes (DEGs) detected between the NILs, 12.7% was located on the single chromosome 3B. Of the expressed genes containing SNP (SNP-EGs) detected, 23.5% was mapped to this chromosome. Several of the DEGs and SNP-EGs are known to be involved in host-pathogen interactions, and a large number of the DEGs were among those detected for FHB in previous studies. Of the DEGs detected, 22 were mapped in the Qcrs-3B interval and they included eight which were detected in the resistant isolines only. The enrichment of DEG, and not necessarily those containing SNPs between the resistant and susceptible isolines, around the Qcrs-3B locus is suggestive of local regulation of this region by the resistance allele. Functions for 13 of these DEGs are known. Of the SNP-EGs, 28 were mapped in the Qcrs-3B interval and biological functions for 16 of them are known. These results provide insights into responses regulated by the 3BL locus and identify a tractable number of target genes for fine mapping and functional testing to identify the causative gene(s) at this QTL.

Multiparental populations are of considerable interest in high-density genetic mapping due to their increased levels of polymorphism and recombination relative to biparental populations. However, errors in map construction can have significant impact on QTL discovery in later stages of analysis, and few methods have been developed to quantify the uncertainty attached to the reported order of markers or intermarker distances. Current methods are computationally intensive or limited to assessing uncertainty only for order or distance, but not both simultaneously. We derive the asymptotic joint distribution of maximum composite likelihood estimators for intermarker distances. This approach allows us to construct hypothesis tests and confidence intervals for simultaneously assessing marker-order instability and distance uncertainty. We investigate the effects of marker density, population size, and founder distribution patterns on map confidence in multiparental populations through simulations. Using these data, we provide guidelines on sample sizes necessary to map markers at sub-centimorgan densities with high certainty. We apply these approaches to data from a bread wheat Multiparent Advanced Generation Inter-Cross (MAGIC) population genotyped using the Illumina 9K SNP chip to assess regions of uncertainty and validate them against the recently released pseudomolecule for the wheat chromosome 3B.

We present a novel estimator for map construction in the presence of segregation distortion which is highly computationally efficient. For multi-parental designs this estimator outperforms methods that do not account for segregation distortion, at no extra computational cost. Inclusion of genetic markers exhibiting segregation distortion in a linkage map can result in biased estimates of genetic distance and distortion of map positions. Removal of distorted markers is hence a typical filtering criterion; however, this may result in exclusion of biologically interesting regions of the genome such as introgressions and translocations. Estimation of additional parameters characterizing the distortion is computationally slow, as it relies on estimation via the Expectation Maximization algorithm or a higher dimensional numerical optimisation. We propose a robust M-estimator (RM) capable of handling tens of thousands of distorted markers from a single linkage group. We show via simulation that for multi-parental designs the RM estimator can perform much better than uncorrected estimation, at no extra computational cost. We then apply the RM estimator to chromosome 2B in wheat in a multi-parent population segregating for the Sr36 introgression, a known transmission distorter. The resulting map contains over 700 markers, and is consistent with maps constructed from crosses which do not exhibit segregation distortion.

An efficient whole genome method of QTL analysis is presented for Multi-parent advanced generation integrated crosses. Multi-parent advanced generation inter-cross (MAGIC) populations have been developed for mice and several plant species and are useful for the genetic dissection of complex traits. The analysis of quantitative trait loci (QTL) in these populations presents some additional challenges compared with traditional mapping approaches. In particular, pedigree and marker information need to be integrated and founder genetic data needs to be incorporated into the analysis. Here, we present a method for QTL analysis that utilizes the probability of inheriting founder alleles across the whole genome simultaneously, either for intervals or markers. The probabilities can be found using three-point or Hidden Markov Model (HMM) methods. This whole-genome approach is evaluated in a simulation study and it is shown to be a powerful method of analysis. The HMM probabilities lead to low rates of false positives and low bias of estimated QTL effect sizes. An implementation of the approach is available as an R package. In addition, we illustrate the approach using a bread wheat MAGIC population.

Identification of alleles towards the selection for improved seedling vigour is a key objective of many wheat breeding programmes. A multiparent advanced generation intercross (MAGIC) population developed from four commercial spring wheat cultivars (cvv. Baxter, Chara, Westonia and Yitpi) and containing ca. 1000 F(2) -derived, F(6:7) RILs was assessed at two contrasting soil temperatures (12 and 20 °C) for shoot length and coleoptile characteristics length and thickness. Narrow-sense heritabilities were high for coleoptile and shoot length (h(2) = 0.68-0.70), indicating a strong genetic basis for the differences among progeny. Genotypic variation was large, and distributions of genotype means were approximately Gaussian with evidence for transgressive segregation for all traits. A number of significant QTL were identified for all early growth traits, and these were commonly repeatable across the different soil temperatures. The largest negative effects on coleoptile lengths were associated with Rht-B1b (-8.2%) and Rht-D1b (-10.9%) dwarfing genes varying in the population. Reduction in coleoptile length with either gene was particularly large at the warmer soil temperature. Other large QTL for coleoptile length were identified on chromosomes 1A, 2B, 4A, 5A and 6B, but these were relatively smaller than allelic effects at the Rht-B1 and Rht-D1 loci. A large coleoptile length effect allele (a = 5.3 mm at 12 °C) was identified on chromosome 1AS despite the relatively shorter coleoptile length of the donor Yitpi. Strong, positive genetic correlations for coleoptile and shoot lengths (r(g) = 0.85-0.90) support the co-location of QTL for these traits and suggest a common physiological basis for both. The multiparent population has enabled the identification of promising shoot and coleoptile QTL despite the potential for the confounding of large effect dwarfing gene alleles present in the commercial parents. The incidence of these alleles in commercial wheat breeding programmes should facilitate their ready implementation in selection of varieties with improved establishment and early growth.

Selective phenotyping is a way of capturing the benefits of large population sizes without the need to carry out large-scale phenotyping and hence is a cost-effective means of capturing information about gene–trait relationships within a population. The diversity within the sample gives an indication of the efficiency of this information capture; less diversity implies greater redundancy of the genetic information. Here, we propose a method to maximize genetic diversity within the selected samples. Our method is applicable to general experimental designs and robust to common problems such as missing data and dominant markers. In particular, we discuss its application to multi-parent advanced generation intercross (MAGIC) populations, where, although thousands of lines may be genotyped as a large population resource, only hundreds may need to be phenotyped for individual studies. Through simulation, we compare our method to simple random sampling and the minimum moment aberration method. While the gain in power over simple random sampling for all tested methods is not large, our method results in a much more diverse sample of genotypes. This diversity can be applied to improve fine mapping resolution once a QTL region has been detected. Further, when applied to two wheat datasets from doubled haploid and MAGIC progeny, our method detects known QTL for small sample sizes where other methods fail.

This paper presents a summary and overview of heterogeneous algorithms and applications developed by the Commonwealth Scientific and Industrial Research Organisation CSIRO for solving practical and challenging science problems such as: 1 high-content analysis of brain cell images for medical research and drug discovery; 2 genetic analysis of complex experimental designs for crop breeding; 3 solving computational fluid dynamics problems; 4 deconvolving 3D images from microscopy and medical imaging; 5 reconstructing large 3D computed tomography CT images from medical and materials science; 6 quantifying uncertainty in complex environmental models. Applications discussed utilise GPUs and multicore CPUs on a scale ranging from single desktop workstations through to large GPU clusters. Results demonstrate that both types of system can successfully accelerate a variety of practical science applications. We have seen significant gains in productivity and opportunity as a result of leveraging GPUs, tackling computational problems in which execution time was previously infeasible.

Wheat is one of the most important cereal crops of the world. In order to achieve continued genetic gain in wheat improvement programs, an assessment and utilisation of genetic diversity in a wide range of germplasm are required. The Australian Winter Cereal Collection (AWCC, Tamworth) holds over 33 000 accessions of wheat. In this study, we scanned the genome of 1057 accessions of hexaploid common wheat (Triticum aestivum L.) originating from different geographic regions of the world, with 178 polymorphic DArT™ markers. These accessions comprised modern cultivars (MCs), advanced breeding lines (BLs), and landrace cultivars (LCs). Our results indicate that the LCs had higher polymorphic information content (PIC values) than the MCs and BLs. Cluster and principal coordinate analysis based on genetic distance matrices enabled classification of the 1057 accessions into 12 subgroups. The structure of subgroups appeared to be geographically determined and was generally consistent with pedigrees. Molecular analyses revealed that LCs have unique alleles compared with MCs and BLs, which may be useful for the genetic improvement of wheat.

An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified. A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

A male sheep linkage map comprising 191 microsatellites was generated from a single family of 510 Awassi-Merino backcross progeny. Except for ovine chromosomes 1, 2, 10 and 17, all other chromosomes yielded a LOD score difference greater than 3.0 between the best and second-best map order. The map is on average 11% longer than the Sheep Linkage Map v4.7 male-specific map. This map was employed in quantitative trait loci (QTL) analyses on body-weight and growth-rate traits between birth and 98 weeks of age. A custom maximum likelihood program was developed to map QTL in half-sib families for non-inbred strains (QTL-MLE) and is freely available on request. The new analysis package offers the advantage of enabling QTL × fixed effect interactions to be included in the model. Fifty-four putative QTL were identified on nine chromosomes. Significant QTL with sex-specific effects (i.e. QTL × sex interaction) in the range of 0.4 to 0.7 SD were found on ovine chromosomes 1, 3, 6, 11, 21, 23, 24 and 26.

Background: Measuring grain characteristics is an integral component of cereal breeding and research into genetic control of seed development. Measures such as thousand grain weight are fast, but do not give an indication of variation within a sample. Other methods exist for detailed analysis of grain size, but are generally costly and very low throughput. Grain colour analysis is generally difficult to perform with accuracy, and existing methods are expensive and involved. Results: We have developed a software method to measure grain size and colour from images captured with consumer level flatbed scanners, in a robust, standardised way. The accuracy and precision of the method have been demonstrated through screening wheat and Brachypodium distachyon populations for variation in size and colour. Conclusion: By using GrainScan, cheap and fast measurement of grain colour and size will enable plant research programs to gain deeper understanding of material, where limited or no information is currently available.