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Developing new crop varieties with superior performance is highly important to ensure robust and sustainable global food security. The speed of variety development is limited by long field cycles and advanced generation selections in plant breeding programs. While methods to predict yield from genotype or phenotype data have been proposed, improved performance and integrated models are needed.

We propose a machine learning model that leverages both genotype and phenotype measurements by fusing genetic variants with multiple data sources collected by unmanned aerial systems. We use a deep multiple instance learning framework with an attention mechanism that sheds light on the importance given to each input during prediction, enhancing interpretability. Our model reaches 0.754 ± 0.024 Pearson correlation coefficient when predicting yield in similar environmental conditions; a 34.8% improvement over the genotype-only linear baseline (0.559 ± 0.050). We further predict yield on new lines in an unseen environment using only genotypes, obtaining a prediction accuracy of 0.386 ± 0.010, a 13.5% improvement over the linear baseline. Our multi-modal deep learning architecture efficiently accounts for plant health and environment, distilling the genetic contribution and providing excellent predictions. Yield prediction algorithms leveraging phenotypic observations during training therefore promise to improve breeding programs, ultimately speeding up delivery of improved varieties.

Available at https://github.com/BorgwardtLab/PheGeMIL (code) and https://doi.org/doi:10.5061/dryad.kprr4xh5p (data).

 

A common pattern of control in firms is for management to retain a broad set of rights, whereas the remaining stakeholders’ contracts provide them with targeted veto rights over specific classes of decisions. We explain this pattern of control sharing as an efficient organizational response that balances the need to encourage management to account for stakeholders’ interests against the need to prevent self-interested stakeholders from blocking valuable proposals. Enforceable obligations of good faith and fair dealing play an essential role in facilitating undivided management control of many decisions. With these legal protections (but not without them), shared control is more likely when the parties are more symmetrically informed and hence, better able to bargain to efficient decisions. This paper was accepted by Joshua Gans, business strategy. 

The wheat wild relativeAegilops tauschiiwas previously used to transfer theLr42leaf rust resistance gene into bread wheat.Lr42confers resistance at both seedling and adult stages, and it is broadly effective against all leaf rust races tested to date.Lr42has been used extensively in the CIMMYT international wheat breeding program with resulting cultivars deployed in several countries. Here, using a bulked segregant RNA-Seq (BSR-Seq) mapping strategy, we identify three candidate genes forLr42. Overexpression of a nucleotide-binding site leucine-rich repeat (NLR) gene AET1Gv20040300 induces strong resistance to leaf rust in wheat and a mutation of the gene disrupted the resistance. TheLr42resistance allele is rare inAe. tauschiiand likely arose from ectopic recombination. Cloning ofLr42provides diagnostic markers and over 1000 CIMMYT wheat lines carryingLr42have been developed documenting its widespread use and impact in crop improvement.

 

Twelve new azole compounds were synthesized through an ene reaction involving methylidene heterocycles and phenylmaleimide, producing four oxazoles, five thiazoles, and one pyridine derivative, and ethyl glyoxylate for an oxazole and a thiazole compound. The twelve azoles have a stereogenic center in their structure. Hence, a method to separate the enantiomeric pairs, must be provided if any further study of chemical and pharmacological importance of these compounds is to be accomplished. Six chiral stationary phases were assayed: four were based on macrocyclic glycopeptide selectors and two on linear carbohydrates, i.e., derivatized maltodextrin and amylose. The enantiomers of the entire set of new chiral azole compounds were separated using three different mobile phase elution modes: normal phase, polar organic, and reversed phase. The most effective chiral stationary phase was the MaltoShell column, which was able to separate ten of the twelve compounds in one elution mode or another. Structural similarities in the newly synthesized oxazoles provided some insights into possible chiral recognition mechanisms. 

Abstract Key message The first cytological characterization of the 2N v S segment in hexaploid wheat; complete de novo assembly and annotation of 2N v S segment; 2N v S frequency is increasing 2N v S and is associated with higher yield. Abstract The Aegilops ventricosa 2N v S translocation segment has been utilized in breeding disease-resistant wheat crops since the early 1990s. This segment is known to possess several important resistance genes against multiple wheat diseases including root knot nematode, stripe rust, leaf rust and stem rust. More recently, this segment has been associated with resistance to wheat blast, an emerging and devastating wheat disease in South America and Asia. To date, full characterization of the segment including its size, gene content and its association with grain yield is lacking. Here, we present a complete cytological and physical characterization of this agronomically important translocation in bread wheat. We de novo assembled the 2N v S segment in two wheat varieties, ‘Jagger’ and ‘CDC Stanley,’ and delineated the segment to be approximately 33 Mb. A total of 535 high-confidence genes were annotated within the 2N v S region, with > 10% belonging to the nucleotide-binding leucine-rich repeat (NLR) gene families. Identification of groups of NLR genes that are potentially N genome-specific and expressed in specific tissues can fast-track testing of candidate genes playing roles in various disease resistances. We also show the increasing frequency of 2N v S among spring and winter wheat breeding programs over two and a half decades, and the positive impact of 2N v S on wheat grain yield based on historical datasets. The significance of the 2N v S segment in wheat breeding due to resistance to multiple diseases and a positive impact on yield highlights the importance of understanding and characterizing the wheat pan-genome for better insights into molecular breeding for wheat improvement. 

Breeding programs for wheat (Triticum aestivumL.) and other crops require one or more generations of seed increase before replicated trials can be sown to assess yield. Extensive phenotyping at this stage is challenging because of the small sizes of plots and large numbers of lines under evaluation, and therefore, breeders typically rely on visual selection to promote lines to yield evaluation. Aerial high‐throughput phenotyping (HTP) enables the rapid acquisition of traits that may be useful for selection among early generation lines. With the objective of assessing the potential for aerial measurements recorded on seed increase plots to improve indirect selection for grain yield (GY), two sets of 1,008 early generation bread wheat breeding lines were sown both as replicated yield trials (YTs) and as small, unreplicated plots (SPs) at the International Maize and Wheat Improvement Center during two breeding cycles. Normalized difference vegetation indices (NDVI) collected with an unmanned aerial vehicle (UAV) in the SPs were observed to be heritable and moderately correlated with GY assessed in YTs. Furthermore, NDVI was more predictive of GY than univariate genomic selection (GS), with still higher overall predictive abilities from multitrait approaches. A related experiment showed that selection based on NDVI would have outperformed visual selection, though this approach would have driven a directional response in phenology because of confounding between phenology, NDVI, and GY. A restricted selection index was proposed to address this issue. These results provide a promising outlook for the use of aerial HTP to improve selection at the early generation, seed‐limited stages of breeding programs.