Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars.

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genome-wide association studies in wheat.

The genetics of rhizosheath size in a multiparent mapping population of wheat.

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 in crops: current status and future prospects.

KEY MESSAGE: 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.

Use of a large multiparent wheat mapping population in genomic dissection of coleoptile and seedling growth.

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.

Computationally efficient map construction in the presence of segregation distortion.

KEY MESSAGE: 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.

Whole-genome QTL analysis for MAGIC.

KEY MESSAGE: 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.

A multiparent advanced generation inter-cross population for genetic analysis in wheat.

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.

Down-regulation of Glucan, Water-Dikinase activity in wheat endosperm increases vegetative biomass and yield.

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.

Bread matters: a national initiative to profile the genetic diversity of Australian wheat.

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.

Sponge and dough bread making: genetic and phenotypic relationships with wheat quality traits.

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.

Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL.

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.

Alternative splicing, activation of cryptic exons and amino acid substitutions in carotenoid biosynthetic genes are associated with lutein accumulation in wheat endosperm.

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.

Increased accuracy of starch granule type quantification using mixture distributions.

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.

Whole-genome analysis of multienvironment or multitrait QTL in MAGIC.

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.

Characterizing uncertainty in high-density maps from multiparental populations.

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.

GrainScan: a low cost, fast method for grain size and colour measurements.

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.