The coordinated expression of highly related homoeologous genes in polyploid species underlies the phenotypes of many of the world's major crops. Here we combine extensive gene expression datasets to produce a comprehensive, genome-wide analysis of homoeolog expression patterns in hexaploid bread wheat. Bias in homoeolog expression varies between tissues, with ~30% of wheat homoeologs showing nonbalanced expression. We found expression asymmetries along wheat chromosomes, with homoeologs showing the largest inter-tissue, inter-cultivar, and coding sequence variation, most often located in high-recombination distal ends of chromosomes. These transcriptionally dynamic genes potentially represent the first steps toward neo- or subfunctionalization of wheat homoeologs. Coexpression networks reveal extensive coordination of homoeologs throughout development and, alongside a detailed expression atlas, provide a framework to target candidate genes underpinning agronomic traits in wheat.

Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production.

Understanding the function of genes within staple crops will accelerate crop improvement by allowing targeted breeding approaches. Despite their importance, a lack of genomic information and resources has hindered the functional characterisation of genes in major crops. The recent release of high-quality reference sequences for these crops underpins a suite of genetic and genomic resources that support basic research and breeding. For wheat, these include gene model annotations, expression atlases and gene networks that provide information about putative function. Sequenced mutant populations, improved transformation protocols and structured natural populations provide rapid methods to study gene function directly. We highlight a case study exemplifying how to integrate these resources. This review provides a helpful guide for plant scientists, especially those expanding into crop research, to capitalise on the discoveries made in Arabidopsis and other plants. This will accelerate the improvement of crops of vital importance for food and nutrition security.

Summary Improving traits in wheat has historically been challenging due to its large and polyploid genome, limited genetic diversity and in‐field phenotyping constraints. However, within recent years many of these barriers have been lowered. The availability of a chromosome‐level assembly of the wheat genome now facilitates a step‐change in wheat genetics and provides a common platform for resources, including variation data, gene expression data and genetic markers. The development of sequenced mutant populations and gene‐editing techniques now enables the rapid assessment of gene function in wheat directly. The ability to alter gene function in a targeted manner will unmask the effects of homoeolog redundancy and allow the hidden potential of this polyploid genome to be discovered. New techniques to identify and exploit the genetic diversity within wheat wild relatives now enable wheat breeders to take advantage of these additional sources of variation to address challenges facing food production. Finally, advances in phenomics have unlocked rapid screening of populations for many traits of interest both in greenhouses and in the field. Looking forwards, integrating diverse data types, including genomic, epigenetic and phenomics data, will take advantage of big data approaches including machine learning to understand trait biology in wheat in unprecedented detail.

Senescence is a tightly regulated developmental program coordinated by transcription factors. Identifying these transcription factors in crops will provide opportunities to tailor the senescence process to different environmental conditions and regulate the balance between yield and grain nutrient content. Here, we use ten time points of gene expression data along with gene network modeling to identify transcription factors regulating senescence in polyploid wheat (Triticum aestivum). We observe two main phases of transcriptional changes during senescence: early down-regulation of housekeeping functions and metabolic processes followed by up-regulation of transport and hormone-related genes. These two phases are largely conserved with Arabidopsis (Arabidopsis thaliana), although the individual genes underlying these changes are often not orthologous. We have identified transcription factor families associated with these early and later waves of differential expression. Using gene regulatory network modeling, we identified candidate transcription factors that may control senescence. Using independent, publicly available datasets, we found that the most highly ranked candidate genes in the network were enriched for senescencerelated functions compared with all genes in the network. We validated the function of one of these candidate transcription factors in senescence using wheat chemically induced mutants. This study lays the groundwork to understand the transcription factors that regulate senescence in polyploid wheat and exemplifies the integration of time-series data with publicly available expression atlases and networks to identify candidate regulatory genes.

Many important genes in agriculture correspond to transcription factors (TFs) that regulate a wide range of pathways from flowering to responses to disease and abiotic stresses. In this study, we identified 5776 TFs in hexaploid wheat (Triticum aestivum) and classified them into gene families. We further investigated the NAC family exploring the phylogeny, C-terminal domain (CTD) conservation, and expression profiles across 308 RNA-seq samples. Phylogenetic trees of NAC domains indicated that wheat NACs divided into eight groups similar to rice (Oryza sativa) and barley (Hordeum vulgare). CTD motifs were frequently conserved between wheat, rice, and barley within phylogenetic groups; however, this conservation was not maintained across phylogenetic groups. Three homeologous copies were present for 58% of NACs, whereas evidence of single homeolog gene loss was found for 33% of NACs. We explored gene expression patterns across a wide range of developmental stages, tissues, and abiotic stresses. We found that more phylogenetically related NACs shared more similar expression patterns compared to more distant NACs. However, within each phylogenetic group there were clades with diverse expression profiles. We carried out a coexpression analysis on all wheat genes and identified 37 modules of coexpressed genes of which 23 contained NACs. Using gene ontology (GO) term enrichment, we obtained putative functions for NACs within coexpressed modules including responses to heat and abiotic stress and responses to water: these NACs may represent targets for breeding or biotechnological applications. This study provides a framework and data for hypothesis generation for future studies on NAC TFs in wheat.

10Senescence is a tightly regulated developmental programme which is coordinated by transcription 11 factors. Identifying these transcription factors in crops will provide opportunities to tailor the 12 senescence process to different environmental conditions and regulate the balance between yield and 13 grain nutrient content. Here we use ten time points of gene expression data alongside gene network 14 modelling to identify transcription factors regulating senescence in polyploid wheat. We observe two 15 main phases of transcription changes during senescence: early downregulation of housekeeping and 16 metabolic processes followed by upregulation of transport and hormone related genes. We have 17identified transcription factor families associated with these early and later waves of differential 18 expression. Using gene regulatory network modelling alongside complementary publicly available 19 datasets we identified candidate transcription factors for controlling senescence. We validated the 20 function of one of these candidate transcription factors in senescence using wheat chemically-induced 21 mutants. This study lays the ground work to understand the transcription factors which regulate 22 senescence in polyploid wheat and exemplifies the integration of time-series data with publicly 23 available expression atlases and networks to identify candidate regulatory genes. 24 25

ARTICLE SUMMARYTranscription factors are vital in plants to regulate gene expression in response to environmental stimuli and to control developmental processes. In this study, we annotated and classified transcription factors in polyploid bread wheat into gene families and explored the NAC family in detail. We combined phylogenetic analysis and transcriptome analysis, using publicly available RNA-seq data, to characterize the NAC gene family and provide hypotheses for putative functions of many NAC transcription factors. This study lays the groundwork for future studies on transcription factors in wheat which may be of great agronomic relevance.ABSTRACTMany important genes in agriculture correspond to transcription factors which regulate a wide range of pathways from flowering to responses to disease and abiotic stresses. In this study, we identified 5,776 transcription factors in hexaploid wheat (Triticum aestivum) and classified them into gene families. We further investigated the NAC family exploring the phylogeny, C-terminal domain conservation and expression profiles across 308 RNA-seq samples. Phylogenetic trees of NAC domains indicated that wheat NACs divided into eight groups similar to rice (Oryza sativa) and barley (Hordeum vulgare). C-terminal domain motifs were frequently conserved between wheat, rice and barley within phylogenetic groups, however this conservation was not maintained across phylogenetic groups. We explored gene expression patterns across a wide range of developmental stages, tissues, and abiotic stresses. We found that more phylogenetically related NACs shared more similar expression patterns compared to more distant NACs. However, within each phylogenetic group there were clades with diverse expression profiles. We carried out a co-expression analysis on all wheat genes and identified 37 modules of co-expressed genes of which 23 contained NACs. Using GO term enrichment we obtained putative functions for NACs within co-expressed modules including responses to heat and abiotic stress and responses to water: these NACs may represent targets for breeding or biotechnological applications. This study provides a framework and data for hypothesis generation for future studies on NAC transcription factors in wheat.