Physical Mapping of QTLs for Root Traits in a Population of Recombinant Inbred Lines of Hexaploid Wheat.

Root architecture is key in determining how effective plants are at intercepting and absorbing nutrients and water. Previously, the wheat (Triticum aestivum) cultivars Spica and Maringa were shown to have contrasting root morphologies. These cultivars were crossed to generate an F6:1 population of recombinant inbred lines (RILs) which was genotyped using a 90 K single nucleotide polymorphisms (SNP) chip. A total of 227 recombinant inbred lines (RILs) were grown in soil for 21 days in replicated trials under controlled conditions. At harvest, the plants were scored for seven root traits and two shoot traits. An average of 7.5 quantitative trait loci (QTL) were associated with each trait and, for each of these, physical locations of the flanking markers were identified using the Chinese Spring reference genome. We also compiled a list of genes from wheat and other monocotyledons that have previously been associated with root growth and morphology to determine their physical locations on the Chinese Spring reference genome. This allowed us to determine whether the QTL discovered in our study encompassed genes previously associated with root morphology in wheat or other monocotyledons. Furthermore, it allowed us to establish if the QTL were co-located with the QTL identified from previously published studies. The parental lines together with the genetic markers generated here will enable specific root traits to be introgressed into elite wheat lines. Moreover, the comprehensive list of genes associated with root development, and their physical locations, will be a useful resource for researchers investigating the genetics of root morphology in cereals.

Adult plant stem rust resistance in durum wheat Glossy Huguenot: mapping, marker development and validation.

KEY MESSAGE: Adult plant stem rust resistance locus, QSrGH.cs-2AL, was identified in durum wheat Glossy Huguenot and mendelised as Sr63. Markers closely linked with Sr63 were developed. An F3 population from a Glossy Huguenot (GH)/Bansi cross used in a previous Australian study was advanced to F6 for molecular mapping of adult plant stem rust resistance. Maturity differences among F6 lines confounded assessments of stem rust response. GH was crossed with a stem rust susceptible F6 recombinant inbred line (RIL), GHB14 (M14), with similar maturity and an F6:7 population was developed through single seed descent method. F7 and F8 RILs were tested along with the parents at different locations. The F6 individual plants and both parents were genotyped using the 90 K single nucleotide polymorphism (SNP) wheat array. Stem rust resistance QTL on the long arms of chromosomes 1B (QSrGH.cs-1BL) and 2A (QSrGH.cs-2AL) were detected. QSrGH.cs-1BL and QSrGH.cs-2AL were both contributed by GH and explained 22% and 18% adult plant stem rust response variation, respectively, among GH/M14 RIL population. RILs carrying combinations of these QTL reduced more than 14% stem rust severity compared to those that possessed QSrGH.cs-1BL and QSrGH.cs-2AL individually. QSrGH.cs1BL was demonstrated to be the same as Sr58/Lr46/Yr29/Pm39 through marker genotyping. Lines lacking QSrGH.cs-1BL were used to Mendelise QSrGH.cs-2AL. Based on genomic locations of previously catalogued stem rust resistance genes and the QSrGH.cs-2AL map, it appeared to represent a new APR locus and was permanently named Sr63. SNP markers associated with Sr63 were converted to kompetetive allele-specific PCR (KASP) assays and were validated on a set of durum cultivars.

Accurate calling of homeoallelic genotypes of iSelect markers using inbred structured populations.

MOTIVATION: Genetic map construction is a foundational step in the analysis of structured experimental populations. For markers that hybridize to several genetically similar locations, or where several alleles are present (such as in multiparental populations), current methods often discard the marker or incorrectly call the genotypes. These errors result in information loss, or incorrect genotypes that can corrupt map construction. RESULTS: We present a new approach for simultaneously performing genetic map construction and marker calling. Our new approach allows the calling of a larger number of markers, a larger number of unique alleles per marker and the correct use of markers which hybridize to multiple genetically similar locations. We demonstrate our new approach using simulations, a biparental wheat population and an eight-parent population of spring bread wheat. Applying our method to the eight-parent population increased the number of mapped markers by 71%. We show that the new genetic map allows the investigation of synteny in ways that were not previously possible in that dataset. AVAILABILITY AND IMPLEMENTATION: The method described in this article has been incorporated into R package mpMap2. It is available from CRAN and also from https://github.com/rohan-shah/mpMap2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A durum wheat adult plant stripe rust resistance QTL and its relationship with the bread wheat Yr80 locus.

KEY MESSAGE: A stripe rust resistance QTL in durum wheat maps near the bread wheat Yr80 locus with the latter reduced to 15 candidate genes. Some wheat adult plant resistance (APR) genes provide partial resistance in the later stages of plant development to rust diseases and are an important component in protecting wheat crops from these fungal pathogens. These genes provide protection in both bread wheat and durum wheat. Here, we have mapped APR to wheat stripe rust, caused by the fungal pathogen Puccinia striiformis f. sp. tritici, in a cross between durum cultivars Stewart and Bansi. Two resistance QTLs derived from the Stewart parent were identified in multi-generational field trials. One QTL is located on chromosome 1BL and maps to the previously identified Yr29/Lr46/Sr58/Pm39 multi-pathogen APR locus. The second locus, located on chromosome 3BL, maps near the recently described bread wheat APR gene, Yr80. Fine mapping in durum and bread wheat families shows that the durum 3BL locus and Yr80 are closely located, with the later APR gene reduced to 15 candidate genes present in the Chinese Spring genome sequence. Distorted segregation of the durum 3BL region was observed with the Stewart locus preferentially transmitted through pollen when compared with the equivalent Bansi region.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding.

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Engineering high α-amylase levels in wheat grain lowers Falling Number but improves baking properties.

Late maturity α-amylase (LMA) and preharvest sprouting (PHS) are genetic defects in wheat. They are both characterized by the expression of specific isoforms of α-amylase in particular genotypes in the grain prior to harvest. The enhanced expression of α-amylase in both LMA and PHS results in a reduction in Falling Number (FN), a test of gel viscosity, and subsequent downgrading of the grain, along with a reduced price for growers. The FN test is unable to distinguish between LMA and PHS; thus, both defects are treated similarly when grain is traded. However, in PHS-affected grains, proteases and other degradative process are activated, and this has been shown to have a negative impact on end product quality. No studies have been conducted to determine whether LMA is detrimental to end product quality. This work demonstrated that wheat in which an isoform α-amylase (TaAmy3) was overexpressed in the endosperm of developing grain to levels of up to 100-fold higher than the wild-type resulted in low FN similar to those seen in LMA- or PHS-affected grains. This increase had no detrimental effect on starch structure, flour composition and enhanced baking quality, in small-scale 10-g baking tests. In these small-scale tests, overexpression of TaAmy3 led to increased loaf volume and Maillard-related browning to levels higher than those in control flours when baking improver was added. These findings raise questions as to the validity of the assumption that (i) LMA is detrimental to end product quality and (ii) a low FN is always indicative of a reduction in quality. This work suggests the need for a better understanding of the impact of elevated expression of specific α-amylase on end product quality.

Suppression of glucan, water dikinase in the endosperm alters wheat grain properties, germination and coleoptile growth.

Starch phosphate ester content is known to alter the physicochemical properties of starch, including its susceptibility to degradation. Previous work producing wheat (Triticum aestivum) with down-regulated glucan, water dikinase, the primary gene responsible for addition of phosphate groups to starch, in a grain-specific manner found unexpected phenotypic alteration in grain and growth. Here, we report on further characterization of these lines focussing on mature grain and early growth. We find that coleoptile length has been increased in these transgenic lines independently of grain size increases. No changes in starch degradation rates during germination could be identified, or any major alteration in soluble sugar levels that may explain the coleoptile growth modification. We identify some alteration in hormones in the tissues in question. Mature grain size is examined, as is Hardness Index and starch conformation. We find no evidence that the increased growth of coleoptiles in these lines is connected to starch conformation or degradation or soluble sugar content and suggest these findings provide a novel means of increasing coleoptile growth and early seedling establishment in cereal crop species.

Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array.

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.

Engineering α-amylase levels in wheat grain suggests a highly sophisticated level of carbohydrate regulation during development.

Wheat starch degradation requires the synergistic action of different amylolytic enzymes. Our spatio-temporal study of wheat α-amylases throughout grain development shows that AMY3 is the most abundant isoform compared with the other known α-amylases. Endosperm-specific over-expression of AMY3 resulted in an increase of total α-amylase activity in harvested grains. Unexpectedly, increased activity did not have a significant impact on starch content or composition but led to an increase of soluble carbohydrate (mainly sucrose) in dry grain. In AMY3 overexpression lines (A3OE), germination was slightly delayed and triacylglycerol (TAG) content was increased in the endosperm of mature grain. Despite increased AMY3 transcript and protein content throughout grain development, alterations of α-amylase activity and starch granule degradation were not detected until grain maturation, suggesting a post-translational inhibition of α-amylase activity in the endosperm during the starch filling period. These findings show unexpected effects of a high level of α-amylase on grain development and composition, notably in carbon partitioning and TAG accumulation, and suggest the presence of a hitherto unknown regulatory pathway during grain filling.

Does Late Maturity Alpha-Amylase Impact Wheat Baking Quality?

Late maturity α-amylase (LMA) and pre-harvest sprouting (PHS) are both recognized as environmentally induced grain quality defects resulting from abnormally high levels of α-amylase. LMA is a more recently identified quality issue that is now receiving increasing attention worldwide and whose prevalence is now seen as impeding the development of superior quality wheat varieties. LMA is a genetic defect present in specific wheat genotypes and is characterized by elevated levels of the high pI TaAMY1 α-amylase, triggered by environmental stress during wheat grain development. TaAMY1 remains present in the aleurone through the harvest, lowering Falling Number (FN) at receival, causing a down-grading of the grain, often to feed grade, thus reducing the farmers' income. This downgrading is based on the assumption within the grain industry that, as for PHS, a low FN represents poor quality grain. Consequently any wheat line possessing low FN or high α-amylase levels is automatically considered a poor bread wheat despite there being no published evidence to date, to show that LMA is detrimental to end product quality. To evaluate the validity of this assumption a comprehensive evaluation of baking properties was performed from LMA prone lines using a subset of tall non-Rht lines from a multi-parent advanced generation inter-cross (MAGIC) wheat population grown at three different sites. LMA levels were determined along with quality parameters including end product functionality such as oven spring, bread loaf volume and weight, slice area and brightness, gas cell number and crumb firmness. No consistent or significant phenotypic correlation was found between LMA related FN and any of the quality traits. This manuscript provides for the first time, compelling evidence that LMA has limited impact on bread baking end product functionality.

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.

Developing data interoperability using standards: A wheat community use case.

In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach's potential to be generalizable to other (agricultural) domains.

Poor Fertility, Short Longevity, and Low Abundance in the Soil Seed Bank Limit Volunteer Sugarcane from Seed.

The recent development of genetically modified sugarcane, with the aim of commercial production, requires an understanding of the potential risks of increased weediness of sugarcane as a result of spread and persistence of volunteer sugarcane. As sugarcane is propagated vegetatively from pieces of stalk and the seed plays no part in the production cycle, the fate of seed in the environment is yet to be studied. In this study, sugarcane seed samples, collected in fields over a 2-year period, were used to determine the overall level of sugarcane fertility, seed dormancy, and longevity of seed under field conditions. A survey of the soil seed bank in and around sugarcane fields was used to quantify the presence of sugarcane seeds and to identify and quantify the weeds that would compete with sugarcane seedlings. We demonstrated that under field conditions, sugarcane has low fertility and produces non-dormant seed. The viability of the seeds decayed rapidly (half-life between 1.5 and 2.1 months). This means that, in Australia, sugarcane seeds die before they encounter climatic conditions that could allow them to germinate and establish. Finally, the soil seed bank analysis revealed that there were very few sugarcane seeds relative to the large number of weed seeds that exert a large competitive effect. In conclusion, low fertility, short persistence, and poor ability to compete limit the capacity of sugarcane seed spread and persistence in the environment.

Transcriptomic analysis of wheat near-isogenic lines identifies PM19-A1 and A2 as candidates for a major dormancy QTL.

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.

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.

Sugarcane genotypes differ in internal nitrogen use efficiency.

The large amounts of nitrogen (N) fertiliser applied to most cropping systems support high yields but cause N pollution. More efficient use of N in cropping systems can be achieved through improved N management practices combined with genetic improvement of the crop. The magnitude of genetic variation in sugarcane (Saccharum officinarum L.) for internal nitrogen use efficiency (iNUE, biomass produced per unit tissue N) was investigated as this could provide a basis for breeding varieties with reduced N demand. Genotypes of a mapping population were examined for biomass production and physiological variables under low or high N supply in controlled conditions. Key findings were: (i) genotypic variation for biomass production and iNUE was up to 3-fold greater under low than high N supply, (ii) elite parent Q165 was among the best performing genotypes for biomass and iNUE at high N but not at low N supply, and (iii) several genotypes had high iNUE at both N supplies. While glutamine synthetase (GS; EC 6.3.1.2) activity has been linked with grain yield in other crops, no direct relationship was observed between whole tissue GS activity and vegetative biomass or iNUE in sugarcane genotypes. Soluble protein content was negatively correlated with iNUE and biomass production. This study demonstrates that there is considerable genetic variation for iNUE in sugarcane, which can be exploited for breeding. It is proposed that breeding programs should assess genotypes not only at high N, but also at low N supply rates to select genotypes that produce high biomass with low and high N supply.