Chromosome-level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates.

Thlaspi arvense (field pennycress) is being domesticated as a winter annual oilseed crop capable of improving ecosystems and intensifying agricultural productivity without increasing land use. It is a selfing diploid with a short life cycle and is amenable to genetic manipulations, making it an accessible field-based model species for genetics and epigenetics. The availability of a high-quality reference genome is vital for understanding pennycress physiology and for clarifying its evolutionary history within the Brassicaceae. Here, we present a chromosome-level genome assembly of var. MN106-Ref with improved gene annotation and use it to investigate gene structure differences between two accessions (MN108 and Spring32-10) that are highly amenable to genetic transformation. We describe non-coding RNAs, pseudogenes and transposable elements, and highlight tissue-specific expression and methylation patterns. Resequencing of forty wild accessions provided insights into genome-wide genetic variation, and QTL regions were identified for a seedling colour phenotype. Altogether, these data will serve as a tool for pennycress improvement in general and for translational research across the Brassicaceae.

Cytogenetic and genomic characterization of a novel tall wheatgrass-derived Fhb7 allele integrated into wheat B genome.

KEY MESSAGE: We identified and integrated the novel FHB-resistant Fhb7The2 allele into wheat B genome and made it usable in both common and durum wheat breeding programs without yellow flour linkage drag. A novel tall wheatgrass-derived (Thinopyrum elongatum, genome EE) Fhb7 allele, designated Fhb7The2, was identified and integrated into the wheat B genome through a small 7B-7E translocation (7BS·7BL-7EL) involving the terminal regions of the long arms. Fhb7The2 conditions significant Type II resistance to Fusarium head blight (FHB) in wheat. Integration of Fhb7The2 into the wheat B genome makes this wild species-derived FHB resistance gene usable for breeding in both common and durum wheat. By contrast, other Fhb7 introgression lines involving wheat chromosome 7D can be utilized only in common wheat breeding programs, not in durum wheat. Additionally, we found that Fhb7The2 does not have the linkage drag of the yellow flour pigment gene that is tightly linked to the decaploid Th. ponticum-derived Fhb7 allele Fhb7Thp. This will further improve the utility of Fhb7The2 in wheat breeding. DNA sequence analysis identified 12 single nucleotide polymorphisms (SNPs) in Fhb7The2, Fhb7Thp, and another Th. elongatum-derived Fhb7 allele Fhb7The1, which led to seven amino acid conversions in Fhb7The2, Fhb7Thp, and Fhb7The1, respectively. However, no significant variation was observed in their predicted protein configuration as a glutathione transferase. Diagnostic DNA markers were developed specifically for Fhb7The2. The 7EL segment containing Fhb7The2 in the translocation chromosome 7BS·7BL-7EL exhibited a monogenic inheritance pattern in the wheat genetic background. This will enhance the efficacy of marker-assisted selection for Fhb7The2 introgression, pyramiding, and deployment in wheat germplasm and varieties.

Soybean Cyst Nematode Population Development and its Effect on Pennycress in a Greenhouse Study.

Midwest crop production is dominated by two summer annual crops grown in rotation, viz., corn (Zea mays L.) and soybean (Glycine max L.). Winter oilseed crops, such as pennycress (Thlaspi arvense L.), can provide ecosystem and economic benefits when added to the corn-soybean rotation. However, adding a new crop adds risks, such as increased pest pressure. The objectives of this study were to (i) evaluate population development of three soybean cyst nematode (SCN; Heterodera glycines) biotypes on three pennycress genotypes and susceptible soybean and (ii) determine whether SCN inoculation level influenced plant biomass. SCN population density and biomass were determined after 60 d in the greenhouse. At the inoculation level of 2,000 eggs/100 cm3 soil, the average egg density for the three pennycress genotypes was 1,959 eggs/100 cm3 soil, lower than that for the susceptible soybean 'Sturdy' (9,601 eggs/100 cm3 soil). At the inoculation level of 20,000 eggs/100 cm3 soil, the average egg density for the three pennycress genotypes was 6,668 eggs/100 cm3 soil, lower than that for 'Sturdy' (40,740 eggs/100 cm3 soil). The inoculation level did not affect plant biomass. Pennycress is an alternative host to SCN under greenhouse conditions but is a less suitable host than soybean.

Translational genomics using Arabidopsis as a model enables the characterization of pennycress genes through forward and reverse genetics.

Thlaspi arvense (pennycress) has the potential for domestication as a new oilseed crop. Information from an extensive body of research on the related plant species Arabidopsis can be used to greatly speed this process. Genome-scale comparisons in this paper documented that pennycress and Arabidopsis share similar gene duplication. This finding led to the hypothesis that it should be possible to isolate Arabidopsis-like mutants in pennycress. This proved to be true, as forward genetic screens identified floral and vegetative pennycress mutants that were similar to mutants found in Arabidopsis. Extending this approach, it was shown that most of the pennycress genes responsible for the formation of oxidized tannins could be rapidly identified. The causative mutations in the pennycress mutants could be identified either by PCR amplification of candidate genes or through whole-genome sequencing (WGS) analysis. In all, WGS was used to characterize 95 ethyl methane sulfonate mutants, which revealed a mutation rate of 4.09 mutations per megabase. A sufficient number of non-synonymous mutations were identified to create a mutant gene index that could be used for reverse genetic approaches to identify pennycress mutants of interest. As proof of concept, a Ta-max3-like dwarf mutant and Ta-kcs5/cer60-like wax mutants deficient in the biosynthesis of long chain fatty acids were identified. Overall, these studies demonstrate that translational genomics can be used to promote the domestication of pennycress. Furthermore, the ease with which important findings could be made in pennycress makes this species a new potential model plant.

Emerging Trends in Wheat (Triticum spp.) Breeding: Implications for the Future.

Wheat (Triticum spp and, particularly, T. aestivum L.) is an essential cereal with increased human and animal nutritional demand. Therefore, there is a need to enhance wheat yield and genetic gain using modern breeding technologies alongside proven methods to achieve the necessary increases in productivity. These modern technologies will allow breeders to develop improved wheat cultivars more quickly and efficiently. This review aims to highlight the emerging technological trends used worldwide in wheat breeding, with a focus on enhancing wheat yield. The key technologies for introducing variation (hybridization among the species, synthetic wheat, and hybridization; genetically modified wheat; transgenic and gene-edited), inbreeding (double haploid (DH) and speed breeding (SB)), selection and evaluation (marker-assisted selection (MAS), genomic selection (GS), and machine learning (ML)) and hybrid wheat are discussed to highlight the current opportunities in wheat breeding and for the development of future wheat cultivars.

GSP-AI: An AI-Powered Platform for Identifying Key Growth Stages and the Vegetative-to-Reproductive Transition in Wheat Using Trilateral Drone Imagery and Meteorological Data.

Wheat (Triticum aestivum) is one of the most important staple crops worldwide. To ensure its global supply, the timing and duration of its growth cycle needs to be closely monitored in the field so that necessary crop management activities can be arranged in a timely manner. Also, breeders and plant researchers need to evaluate growth stages (GSs) for tens of thousands of genotypes at the plot level, at different sites and across multiple seasons. These indicate the importance of providing a reliable and scalable toolkit to address the challenge so that the plot-level assessment of GS can be successfully conducted for different objectives in plant research. Here, we present a multimodal deep learning model called GSP-AI, capable of identifying key GSs and predicting the vegetative-to-reproductive transition (i.e., flowering days) in wheat based on drone-collected canopy images and multiseasonal climatic datasets. In the study, we first established an open Wheat Growth Stage Prediction (WGSP) dataset, consisting of 70,410 annotated images collected from 54 varieties cultivated in China, 109 in the United Kingdom, and 100 in the United States together with key climatic factors. Then, we built an effective learning architecture based on Res2Net and long short-term memory (LSTM) to learn canopy-level vision features and patterns of climatic changes between 2018 and 2021 growing seasons. Utilizing the model, we achieved an overall accuracy of 91.2% in identifying key GS and an average root mean square error (RMSE) of 5.6 d for forecasting the flowering days compared with manual scoring. We further tested and improved the GSP-AI model with high-resolution smartphone images collected in the 2021/2022 season in China, through which the accuracy of the model was enhanced to 93.4% for GS and RMSE reduced to 4.7 d for the flowering prediction. As a result, we believe that our work demonstrates a valuable advance to inform breeders and growers regarding the timing and duration of key plant growth and development phases at the plot level, facilitating them to conduct more effective crop selection and make agronomic decisions under complicated field conditions for wheat improvement.

Genetic dissection of seed characteristics in field pennycress via genome-wide association mapping studies.

Field pennycress (Thlaspi arvense L.) is a new winter annual cash cover crop with high oil content and seed yield, excellent winter hardiness, early maturation, and resistance to most pests and diseases. It provides living cover on fallow croplands between summer seasons, and in doing so reduces nutrient leaching into water sources, mitigates soil erosion, and suppresses weed growth. The first ever genome-wide association study (GWAS) was conducted on a pennycress diversity panel to identify marker trait associations with important seed size and composition related traits. The entire population was phenotyped in three total environments over 2 yr, and seed area, length, width, thousand grain weight, total oil, and total protein were measured post-harvest with specialized high-throughput imaging and near-infrared spectroscopy. Basic unbiased linear prediction values were calculated for each trait. Seed size traits tended to have higher entry mean reliabilities (0.76-0.79) compared with oil content (0.51) and protein content (0.37). Genotyping-by-sequencing identified 33,606 high quality genome-wide single nucleotide polymorphism (SNPs) that were coupled with phenotypic data to perform GWAS for seed area, length, width, thousand grain weight, total oil, and total protein content. Fifty-nine total marker-trait associations were identified revealing genomic regions controlling each trait. The significant SNPs explained 0.06-0.18% of the total variance for that trait in our population. A list of candidate genes was identified based on their functional annotations and characterization in other species. Our results confirm that GWAS is an efficient strategy to identify significant marker-trait associations that can be incorporated into marker-assisted selection pipelines to accelerate pennycress breeding progress.

Field pennycress is an excellent winter annual oilseed that can serve as a cash cover crop. Genotyping-by-sequencing is an effective strategy to genotype pennycress affordably for high-quality genome-wide single nucleotide polymorphisms. First-ever mapping study in a field pennycress association mapping population was conducted. GWAS identified 59 significant marker-trait associations for important quantitative traits. Seed size traits had a higher reliability estimate compared with seed composition traits.

Novel Single-Nucleotide Variants for Morpho-Physiological Traits Involved in Enhancing Drought Stress Tolerance in Barley.

Barley (Hordeum vulgare L.) thrives in the arid and semi-arid regions of the world; nevertheless, it suffers large grain yield losses due to drought stress. A panel of 426 lines of barley was evaluated in Egypt under deficit (DI) and full irrigation (FI) during the 2019 and 2020 growing seasons. Observations were recorded on the number of days to flowering (NDF), total chlorophyll content (CH), canopy temperature (CAN), grain filling duration (GFD), plant height (PH), and grain yield (Yield) under DI and FI. The lines were genotyped using the 9K Infinium iSelect single nucleotide polymorphisms (SNP) genotyping platform, which resulted in 6913 high-quality SNPs. In conjunction with the SNP markers, the phenotypic data were subjected to a genome-wide association scan (GWAS) using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK). The GWAS results indicated that 36 SNPs were significantly associated with the studied traits under DI and FI. Furthermore, eight markers were significant and common across DI and FI water regimes, while 14 markers were uniquely associated with the studied traits under DI. Under DI and FI, three (11_10326, 11_20042, and 11_20170) and five (11_20099, 11_10326, 11_20840, 12_30298, and 11_20605) markers, respectively, had pleiotropic effect on at least two traits. Among the significant markers, 24 were annotated to known barley genes. Most of these genes were involved in plant responses to environmental stimuli such as drought. Overall, nine of the significant markers were previously reported, and 27 markers might be considered novel. Several markers identified in this study could enable the prediction of barley accessions with optimal agronomic performance under DI and FI.

Uncovering the Genetic Architecture of Seed Weight and Size in Intermediate Wheatgrass through Linkage and Association Mapping.

Intermediate wheatgrass [IWG; (Host) Barkworth & D.R. Dewey subsp. ] is being developed as a new perennial grain crop that has a large allohexaploid genome similar to that of wheat ( L.). Breeding for increased seed weight is one of the primary goals for improving grain yield of IWG. As a new crop, however, the genetic architecture of seed weight and size has not been characterized, and selective breeding of IWG may be more intricate than wheat because of its self-incompatible mating system and perennial growth habit. Here, seed weight, seed area size, seed width, and seed length were evaluated across multiple years, in a heterogeneous breeding population comprised of 1126 genets and two clonally replicated biparental populations comprised of 172 and 265 genets. Among 10,171 DNA markers discovered using genotyping-by-sequencing (GBS) in the breeding population, 4731 markers were present in a consensus genetic map previously constructed using seven full-sib populations. Thirty-three quantitative trait loci (QTL) associated with seed weight and size were identified using association mapping (AM), of which 23 were verified using linkage mapping in the biparental populations. About 37.6% of seed weight variation in the breeding population was explained by 15 QTL, 12 of which also contributed to either seed length or seed width. When performing either phenotypic selection or genomic selection for seed weight, we observed the frequency of favorable QTL alleles were increased to >46%. Thus, by combining AM and genomic selection, we can effectively select the favorable QTL alleles for seed weight and size in IWG breeding populations.