Harnessing landrace diversity empowers wheat breeding.

Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A.E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, through whole-genome re-sequencing (827 Watkins landraces and 208 modern cultivars) and in-depth field evaluation spanning a decade. We discovered that modern cultivars are derived from just two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium (LD) based haplotypes and association genetics analyses link Watkins genomes to the thousands of high-resolution quantitative trait loci (QTL), and significant marker-trait associations identified. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritised QTL in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilising genetic diversity in crop improvement to achieve sustainable food security.

Phenomic and genomic prediction of yield on multiple locations in winter wheat.

Genomic selection has recently become an established part of breeding strategies in cereals. However, a limitation of linear genomic prediction models for complex traits such as yield is that these are unable to accommodate Genotype by Environment effects, which are commonly observed over trials on multiple locations. In this study, we investigated how this environmental variation can be captured by the collection of a large number of phenomic markers using high-throughput field phenotyping and whether it can increase GS prediction accuracy. For this purpose, 44 winter wheat (Triticum aestivum L.) elite populations, comprising 2,994 lines, were grown on two sites over 2 years, to approximate the size of trials in a practical breeding programme. At various growth stages, remote sensing data from multi- and hyperspectral cameras, as well as traditional ground-based visual crop assessment scores, were collected with approximately 100 different data variables collected per plot. The predictive power for grain yield was tested for the various data types, with or without genome-wide marker data sets. Models using phenomic traits alone had a greater predictive value (R2 = 0.39-0.47) than genomic data (approximately R2 = 0.1). The average improvement in predictive power by combining trait and marker data was 6%-12% over the best phenomic-only model, and performed best when data from one full location was used to predict the yield on an entire second location. The results suggest that genetic gain in breeding programmes can be increased by utilisation of large numbers of phenotypic variables using remote sensing in field trials, although at what stage of the breeding cycle phenomic selection could be most profitably applied remains to be answered.

Delaying or delivering: identification of novel NAM-1 alleles that delay senescence to extend wheat grain fill duration.

Senescence is a complex trait under genetic and environmental control, in which resources are remobilized from vegetative tissue into grain. Delayed senescence, or 'staygreen' traits, can confer stress tolerance, with extended photosynthetic activity hypothetically sustaining grain filling. The genetics of senescence regulation are largely unknown, with senescence variation often correlated with phenological traits. Here, we confirm staygreen phenotypes of two Triticum aestivum cv. Paragon ethyl methane sulfonate mutants previously identified during a forward genetic screen and selected for their agronomic performance, similar phenology, and differential senescence phenotypes. Grain filling experiments confirmed a positive relationship between onset of senescence and grain fill duration, reporting an associated ~14% increase in final dry grain weight for one mutant (P<0.05). Recombinant inbred line (RIL) populations segregating for the timing of senescence were developed for trait mapping purposes and phenotyped over multiple years under field conditions. Quantification and comparison of senescence metrics aided RIL selection, facilitating exome capture-enabled bulk segregant analysis (BSA). Using BSA we mapped our two staygreen traits to two independent, dominant, loci of 4.8 and 16.7 Mb in size encompassing 56 and 142 genes, respectively. Combining association analysis with variant effect prediction, we identified single nucleotide polymorphisms encoding self-validating mutations located in NAM-1 homoeologues, which we propose as gene candidates.

Capturing and Selecting Senescence Variation in Wheat.

Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation and ultimately identify novel genetic regulators, accurate characterization of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, the visual assessment of flag leaves. However, senescence is a whole-plant process, involving remobilization and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics. To gain a holistic understanding of senescence, we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between-year Spearman's rank correlations of r ≥ 0.59, P < 4.7 × 10-5 (TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognized the need for singular metrics capable of discriminating senescence variation, identifying thermal time to flag leaf senescence score of 70 (TT70) and mean peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality. Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent recombinant inbred line (RIL) populations segregating for staygreen traits. Together, we direct readers toward senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and aid trait selection and weighting in breeding and research programs alike.

Rust expression browser: an open source database for simultaneous analysis of host and pathogen gene expression profiles with expVIP.

BACKGROUND: Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called "field pathogenomics". As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation. RESULTS: Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser ( http://www.rust-expression.com ). This enables for the first time simultaneous 'point-and-click' access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection. CONCLUSIONS: The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available.

Tracing the ancestry of modern bread wheats.

For more than 10,000 years, the selection of plant and animal traits that are better tailored for human use has shaped the development of civilizations. During this period, bread wheat (Triticum aestivum) emerged as one of the world's most important crops. We use exome sequencing of a worldwide panel of almost 500 genotypes selected from across the geographical range of the wheat species complex to explore how 10,000 years of hybridization, selection, adaptation and plant breeding has shaped the genetic makeup of modern bread wheats. We observe considerable genetic variation at the genic, chromosomal and subgenomic levels, and use this information to decipher the likely origins of modern day wheats, the consequences of range expansion and the allelic variants selected since its domestication. Our data support a reconciled model of wheat evolution and provide novel avenues for future breeding improvement.

The effects of training population design on genomic prediction accuracy in wheat.

Genomic selection offers several routes for increasing the genetic gain or efficiency of plant breeding programmes. In various species of livestock, there is empirical evidence of increased rates of genetic gain from the use of genomic selection to target different aspects of the breeder's equation. Accurate predictions of genomic breeding value are central to this, and the design of training sets is in turn central to achieving sufficient levels of accuracy. In summary, small numbers of close relatives and very large numbers of distant relatives are expected to enable predictions with higher accuracy. To quantify the effect of some of the properties of training sets on the accuracy of genomic selection in crops, we performed an extensive field-based winter wheat trial. In summary, this trial involved the construction of 44 F2:4 bi- and tri-parental populations, from which 2992 lines were grown on four field locations and yield was measured. For each line, genotype data were generated for 25 K segregating SNP markers. The overall heritability of yield was estimated to 0.65, and estimates within individual families ranged between 0.10 and 0.85. Genomic prediction accuracies of yield BLUEs were 0.125-0.127 using two different cross-validation approaches and generally increased with training set size. Using related crosses in training and validation sets generally resulted in higher prediction accuracies than using unrelated crosses. The results of this study emphasise the importance of the training panel design in relation to the genetic material to which the resulting prediction model is to be applied.

Cry2 Is Critical for Circadian Regulation of Myogenic Differentiation by Bclaf1-Mediated mRNA Stabilization of Cyclin D1 and Tmem176b.

Circadian rhythms regulate cell proliferation and differentiation; however, little is known about their roles in myogenic differentiation. Our synchronized differentiation studies demonstrate that myoblast proliferation and subsequent myotube formation by cell fusion occur in circadian manners. We found that one of the core regulators of circadian rhythms, Cry2, but not Cry1, is critical for the circadian patterns of these two critical steps in myogenic differentiation. This is achieved through the specific interaction between Cry2 and Bclaf1, which stabilizes mRNAs encoding cyclin D1, a G1/S phase transition regulator, and Tmem176b, a transmembrane regulator for myogenic cell fusion. Myoblasts lacking Cry2 display premature cell cycle exit and form short myotubes because of inefficient cell fusion. Consistently, muscle regeneration is impaired in Cry2-/- mice. Bclaf1 knockdown recapitulated the phenotypes of Cry2 knockdown: early cell cycle exit and inefficient cell fusion. This study uncovers a post-transcriptional regulation of myogenic differentiation by circadian rhythms.

Global phylogenetics of Diuraphis noxia (Hemiptera: Aphididae), an invasive aphid species: evidence for multiple invasions into North America.

The Russian wheat aphid, Diruaphis noxia (Kudjumov) (Hemiptera: Aphididae), is globally one of the most devastating pests of bread wheat, Tritium aestivum L., durum wheat, Triticum turgidum L., and barley, Hordeum vulgare L. Several sources of D. noxia resistance have been incorporated in commercial wheat and barley genotypes, but up to eight virulent biotypes, defined based on their ability to damage different wheat and barley genotypes, now occur across the western United States since the first appearance of D. noxia in North America in 1986. Critical to the study of D. noxia and other invasive species is an understanding of the number and origin of invasions that have occurred, as well as the rate or potential of postinvasion adaptation and geographic range expansion. The goal of this study was to determine whether D. noxia biotypes are by-products of a single invasion or multiple invasions into North America. We used the genome-wide technique of amplified fragment length polymorphisms, in combination with 22 collections of D. noxia from around the world, to assess this question, as well as patterns of genetic divergence. We found multiple lines of evidence that there have been at least two D. noxia invasions of different origin into North America, each resulting in subsequent postinvasion diversification that has since yielded multiple biotypes.