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.
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.
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.
Previous molecular phylogenetic analyses have resolved the Australian bloodwood eucalypt genus Corymbia (~100 species) as either monophyletic or paraphyletic with respect to Angophora (9-10 species). ...Here we assess relationships of Corymbia and Angophora using a large dataset of chloroplast DNA sequences (121,016 base pairs; from 90 accessions representing 55 Corymbia and 8 Angophora species, plus 33 accessions of related genera), skimmed from high throughput sequencing of genomic DNA, and compare results with new analyses of nuclear ITS sequences (119 accessions) from previous studies. Maximum likelihood and maximum parsimony analyses of cpDNA resolve well supported trees with most nodes having >95% bootstrap support. These trees strongly reject monophyly of Corymbia, its two subgenera (Corymbia and Blakella), most taxonomic sections (Abbreviatae, Maculatae, Naviculares, Septentrionales), and several species. ITS trees weakly indicate paraphyly of Corymbia (bootstrap support <50% for maximum likelihood, and 71% for parsimony), but are highly incongruent with the cpDNA analyses, in that they support monophyly of both subgenera and some taxonomic sections of Corymbia. The striking incongruence between cpDNA trees and both morphological taxonomy and ITS trees is attributed largely to chloroplast introgression between taxa, because of geographic sharing of chloroplast clades across taxonomic groups. Such introgression has been widely inferred in studies of the related genus Eucalyptus. This is the first report of its likely prevalence in Corymbia and Angophora, but this is consistent with previous morphological inferences of hybridisation between species. Our findings (based on continent-wide sampling) highlight a need for more focussed studies to assess the extent of hybridisation and introgression in the evolutionary history of these genera, and that critical testing of the classification of Corymbia and Angophora requires additional sequence data from nuclear genomes.
Summary
Until recently, achieving a reference‐quality genome sequence for bread wheat was long thought beyond the limits of genome sequencing and assembly technology, primarily due to the large ...genome size and > 80% repetitive sequence content. The release of the chromosome scale 14.5‐Gb IWGSC RefSeq v1.0 genome sequence of bread wheat cv. Chinese Spring (CS) was, therefore, a milestone. Here, we used a direct label and stain (DLS) optical map of the CS genome together with a prior nick, label, repair and stain (NLRS) optical map, and sequence contigs assembled with Pacific Biosciences long reads, to refine the v1.0 assembly. Inconsistencies between the sequence and maps were reconciled and gaps were closed. Gap filling and anchoring of 279 unplaced scaffolds increased the total length of pseudomolecules by 168 Mb (excluding Ns). Positions and orientations were corrected for 233 and 354 scaffolds, respectively, representing 10% of the genome sequence. The accuracy of the remaining 90% of the assembly was validated. As a result of the increased contiguity, the numbers of transposable elements (TEs) and intact TEs have increased in IWGSC RefSeq v2.1 compared with v1.0. In total, 98% of the gene models identified in v1.0 were mapped onto this new assembly through development of a dedicated approach implemented in the MAGAAT pipeline. The numbers of high‐confidence genes on pseudomolecules have increased from 105 319 to 105 534. The reconciled assembly enhances the utility of the sequence for genetic mapping, comparative genomics, gene annotation and isolation, and more general studies on the biology of wheat.
Significance Statement
This new release of bread wheat cv. Chinese Spring reference genome sequence, IWGSC RefSeq v2.1, features correction of assembly errors affecting approximately 10% of the prior IWGSC RefSeq v1.0 release using genome‐wide optical maps and filling of gaps with single‐molecule long‐reads as well as incorporating re‐annotation of TEs and re‐computation of gene coordinates. These refinements enhance the sequence utility for breeding and research applications.
Crop growth models (CGM) can predict the performance of a cultivar in untested environments by sampling genotype-specific parameters. As they cannot predict the performance of new cultivars, it has ...been proposed to integrate CGMs with whole genome prediction (WGP) to combine the benefits of both models. Here, we used a CGM-WGP model to predict the performance of new wheat (Triticum aestivum) genotypes. The CGM was designed to predict phenology, nitrogen, and biomass traits. The CGM-WGP model simulated more heritable GSPs compared with the CGM and gave smaller errors for the observed phenotypes. The WGP model performed better when predicting yield, grain number, and grain protein content, but showed comparable performance to the CGM-WGP model for heading and physiological maturity dates. However, the CGM-WGP model was able to predict unobserved traits (for which there were no phenotypic records in the reference population). The CGM-WGP model also showed superior performance when predicting unrelated individuals that clustered separately from the reference population. Our results demonstrate new advantages for CGM-WGP modelling and suggest future efforts should focus on calibrating CGM-WGP models using high-throughput phenotypic measures that are cheaper and less laborious to collect.
Abstract
Running crop growth models (CGM) coupled with whole genome prediction (WGP) as a CGM–WGP model introduces environmental information to WGP and genomic relatedness information to the ...genotype-specific parameters modelled through CGMs. Previous studies have primarily used CGM–WGP to infer prediction accuracy without exploring its potential to enhance CGM and WGP. Here, we implemented a heading and maturity date wheat phenology model within a CGM–WGP framework and compared it with CGM and WGP. The CGM–WGP resulted in more heritable genotype-specific parameters with more biologically realistic correlation structures between genotype-specific parameters and phenology traits compared with CGM-modelled genotype-specific parameters that reflected the correlation of measured phenotypes. Another advantage of CGM–WGP is the ability to infer accurate prediction with much smaller and less diverse reference data compared with that required for CGM. A genome-wide association analysis linked the genotype-specific parameters from the CGM–WGP model to nine significant phenology loci including Vrn-A1 and the three PPD1 genes, which were not detected for CGM-modelled genotype-specific parameters. Selection on genotype-specific parameters could be simpler than on observed phenotypes. For example, thermal time traits are theoretically more independent candidates, compared with the highly correlated heading and maturity dates, which could be used to achieve an environment-specific optimal flowering period. CGM–WGP combines the advantages of CGM and WGP to predict more accurate phenotypes for new genotypes under alternative or future environmental conditions.
Integrating crop growth models and genomic prediction offers more accurate simulation of genotype-specific parameters with minimal equifinality even when using phenotypic data from a single field trial.
Pre-harvest sprouting (PHS) is an important cause of quality loss in many cereal crops and is particularly prevalent and damaging in wheat. Resistance to PHS is therefore a valuable target trait in ...many breeding programs. The
locus on wheat chromosome arm 4AL has been consistently shown to account for a significant proportion of natural variation to PHS in diverse mapping populations. However, the deployment of sprouting resistance is confounded by the fact that different candidate genes, including the tandem duplicated
(
) genes and the
(
gene, have been proposed to underlie
. To further define the
locus, we constructed a physical map across this interval in hexaploid and tetraploid wheat. We established close proximity of the proposed candidate genes which are located within a 1.2 Mb interval. Genetic characterization of diverse germplasm used in previous genetic mapping studies suggests that
, and not
, is the major gene underlying the
effect in European, North American, Australian and Asian germplasm. We identified the non-dormant
allele at low frequencies within the A-genome diploid progenitor
genepool, and show an increase in the allele frequency in modern varieties. In United Kingdom varieties, the frequency of the dormant
allele was significantly higher in bread-making quality varieties compared to feed and biscuit-making cultivars. Analysis of exome capture data from 58 diverse hexaploid wheat accessions identified fourteen haplotypes across the extended
locus and four haplotypes for
. Analysis of these haplotypes in a collection of United Kingdom and Australian cultivars revealed distinct major dormant and non-dormant
haplotypes in each country, which were either rare or absent in the opposing germplasm set. The diagnostic markers and haplotype information reported in the study will help inform the choice of germplasm and breeding strategies for the deployment of
resistance into breeding germplasm.
We investigated the benefit from introgression of external lines into a cereal breeding programme and strategies that accelerated introgression of the favourable alleles while minimising linkage drag ...using stochastic computer simulation. We simulated genomic selection for disease resistance and grain yield in two environments with a high level of genotype-by-environment interaction (G × E) for the latter trait, using genomic data of a historical barley breeding programme as the base generation. Two populations (existing and external) were created from this base population with different allele frequencies for few (
N
= 10) major and many (
N
~ 990) minor simulated disease quantitative trait loci (QTL). The major disease QTL only existed in the external population and lines from the external population were introgressed into the existing population which had minor disease QTL with low, medium and high allele frequencies. The study revealed that the benefit of introgression depended on the level of genetic variation for the target trait in the existing cereal breeding programme. Introgression of external resources into the existing population was beneficial only when the existing population lacked variation in disease resistance or when minor disease QTL were already at medium or high frequency. When minor disease QTL were at low frequencies, no extra genetic gain was achieved from introgression. More benefit in the disease trait was obtained from the introgression if the major disease QTL had larger effect sizes, more selection emphasis was applied on disease resistance, or more external lines were introgressed. While our strategies to increase introgression of major disease QTL were generally successful, most were not able to completely avoid negative impacts on selection for grain yield with the only exception being when major introgression QTL effects were very large. Breeding programmes are advised to carefully consider the level of genetic variation in a trait available in their breeding programme before deciding to introgress germplasms.
A novel vegetation index was derived to estimate chlorophyll and was shown to be effective for high-throughput phenotyping of wheat germplasm for nitrogen response.
Abstract
The development of crop ...varieties with higher nitrogen use efficiency is crucial for sustainable crop production. Combining high-throughput genotyping and phenotyping will expedite the discovery of novel alleles for breeding crop varieties with higher nitrogen use efficiency. Digital and hyperspectral imaging techniques can efficiently evaluate the growth, biophysical, and biochemical performance of plant populations by quantifying canopy reflectance response. Here, these techniques were used to derive automated phenotyping of indicator biomarkers, biomass and chlorophyll levels, corresponding to different nitrogen levels. A detailed description of digital and hyperspectral imaging and the associated challenges and required considerations are provided, with application to delineate the nitrogen response in wheat. Computational approaches for spectrum calibration and rectification, plant area detection, and derivation of vegetation index analysis are presented. We developed a novel vegetation index with higher precision to estimate chlorophyll levels, underpinned by an image-processing algorithm that effectively removed background spectra. Digital shoot biomass and growth parameters were derived, enabling the efficient phenotyping of wheat plants at the vegetative stage, obviating the need for phenotyping until maturity. Overall, our results suggest value in the integration of high-throughput digital and spectral phenomics for rapid screening of large wheat populations for nitrogen response.
The moderate to high levels of nucleotide diversity and low linkage disequilibrium found in many forest tree species make them ideal candidates for association mapping. Here, we report candidate ...gene-based association mapping results for complex wood quality and growth traits in Eucalyptus globulus Labill. ssp. globulus, the most widely grown eucalypt in temperate regions of the world. Ninety-eight single nucleotide polymorphisms (SNPs) from 20 wood quality candidate genes were assayed in a discovery population consisting of 385 trees sourced from a provenance-progeny trial. Twenty-five selected SNPs with significant associations (P < 0.05) in the discovery population were assayed for validation in 296 trees sourced from an independent second-generation breeding trial. To account for background genetic structure, mixed models were used in the association analyses. Two associations identified in the discovery population were independently supported in the validation testing. However, combining the discovery and validation results in a combined analysis, we discovered nine stable marker-trait associations for seven traits. These associations link underlying complex wood and growth phenotypes to earlier putative selection signatures opening new avenues to accelerate the dissection of these traits.
Introduction In plant breeding, we often aim to improve multiple traits at once. However, without knowing the economic value of each trait, it is hard to decide which traits to focus on. This is ...where “desired gain selection indices” come in handy, which can yield optimal gains in each trait based on the breeder’s prioritisation of desired improvements when economic weights are not available. However, they lack the ability to maximise the selection response and determine the correlation between the index and net genetic merit. Methods Here, we report the development of an iterative desired gain selection index method that optimises the sampling of the desired gain values to achieve a targeted or a user-specified selection response for multiple traits. This targeted selection response can be constrained or unconstrained for either a subset or all the studied traits. Results We tested the method using genomic estimated breeding values (GEBVs) for seven traits in a bread wheat ( Triticum aestivum ) reference breeding population comprising 3,331 lines and achieved prediction accuracies ranging between 0.29 and 0.47 across the seven traits. The indices were validated using 3,005 double haploid lines that were derived from crosses between parents selected from the reference population. We tested three user-specified response scenarios: a constrained equal weight (INDEX1), a constrained yield dominant weight (INDEX2), and an unconstrained weight (INDEX3). Our method achieved an equivalent response to the user-specified selection response when constraining a set of traits, and this response was much better than the response of the traditional desired gain selection indices method without iteration. Interestingly, when using unconstrained weight, our iterative method maximised the selection response and shifted the average GEBVs of the selection candidates towards the desired direction. Discussion Our results show that the method is an optimal choice not only when economic weights are unavailable, but also when constraining the selection response is an unfavourable option.
PDF
