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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., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., Competing Interests: YL, FS, ZL, GK-G, MH, JT, and HD were employed by the company Agriculture Victoria Services Pty Ltd. HR, DMo, AR, JG, and DMu were employed by the company InterGrain Pty Ltd., (Copyright © 2022 Li, Shi, Lin, Robinson, Moody, Rattey, Godoy, Mullan, Keeble-Gagnere, Hayden, Tibbits and Daetwyler.)

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.

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 Phs-A1 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 Plasma Membrane 19 ( PM19 ) genes and the mitogen-activated protein kinase kinase 3 ( TaMKK3-A) gene, have been proposed to underlie Phs-A1 . To further define the Phs-A1 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 TaMKK3-A , and not PM19 , is the major gene underlying the Phs-A1 effect in European, North American, Australian and Asian germplasm. We identified the non-dormant TaMKK3-A allele at low frequencies within the A-genome diploid progenitor Triticum urartu genepool, and show an increase in the allele frequency in modern varieties. In United Kingdom varieties, the frequency of the dormant TaMKK3-A 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 Phs-A1 locus and four haplotypes for TaMKK3-A . Analysis of these haplotypes in a collection of United Kingdom and Australian cultivars revealed distinct major dormant and non-dormant Phs-A1 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 Phs-A1 resistance into breeding germplasm.

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.

Cellulose microfibrils are the major structural component of plant secondary cell walls. Their arrangement in plant primary cell walls, and its consequent influence on cell expansion and cellular morphology, is directed by cortical microtubules; cylindrical protein filaments composed of heterodimers of alpha- and beta-tubulin. In secondary cell walls of woody plant stems the orientation of cellulose microfibrils influences the strength and flexibility of wood, providing the physical support that has been instrumental in vascular plant colonization of the troposphere. Here we show that a Eucalyptus grandisbeta-tubulin gene (EgrTUB1) is involved in determining the orientation of cellulose microfibrils in plant secondary fibre cell walls. This finding is based on RNA expression studies in mature trees, where we identified and isolated EgrTUB1 as a candidate for association with wood-fibre formation, and on the analysis of somatically derived transgenic wood sectors in Eucalyptus. We show that cellulose microfibril angle (MFA) is correlated with EgrTUB1 expression, and that MFA was significantly altered as a consequence of stable transformation with EgrTUB1. Our findings present an important step towards the production of fibres with altered tensile strength, stiffness and elastic properties, and shed light on one of the molecular mechanisms that has enabled trees to dominate terrestrial ecosystems.