Search

Two homoeologous QTLs for number of spikelets per spike (SPS) were mapped on chromosomes 7AL and 7BL using two wheat MAGIC populations. Sets of lines contrasting for the QTL on 7AL were developed which allowed for the validation and fine mapping of the 7AL QTL and for the identification of a previously described candidate gene, WHEAT ORTHOLOG OF APO1 (WAPO1). Using transgenic overexpression in both a low and a high SPS line, we provide a functional validation for the role of this gene in determining SPS also in hexaploid wheat. We show that the expression levels of this gene positively correlate with SPS in multiple MAGIC founder lines under field conditions as well as in transgenic lines grown in the greenhouse. This work highlights the potential use of WAPO1 in hexaploid wheat for further yield increases. The impact of WAPO1 and SPS on yield depends on other genetic and environmental factors, hence, will require a finely balanced expression level to avoid the development of detrimental pleiotropic phenotypes. [ABSTRACT FROM AUTHOR]

Key message: We present new association mapping methods which address the unique challenges of analyzing genome-wide data from multi-environment plant studies. Abstract: 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. [ABSTRACT FROM AUTHOR]

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. Abstract: 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. [ABSTRACT FROM AUTHOR]

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. Abstract: 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. [ABSTRACT FROM AUTHOR]

Key message: An efficient whole genome method of QTL analysis is presented for Multi-parent advanced generation integrated crosses. Abstract: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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, ε-cyclase ( ε-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 ε-LCY and Psy-A1 revealed possible causal mechanisms for both QTL. A point mutation in ε−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. [ABSTRACT FROM AUTHOR]

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 harvesting1. 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 barley2-5. 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. [ABSTRACT FROM AUTHOR]