Are There Adequate Incentives for Research and Innovation in the Plant Breeding Supply Chain?

The breeding supply chain has expanded with genomic technology to include basic research scientists and applied genomicists along with traditional plant breeders and farmers. Genomicists have focused on identifying specific DNA sequences or quantitative trait loci (QTL) that can be used as molecular markers. However, the use of molecular marker-assisted selection (MAS) by breeders in their programs requires the identified QTL to be reliably correlated with agronomically desirable traits. Replication research is critical for reducing the risk associated with the adoption of new marker-based (or QTL-based) selection strategies, but the applied scientists doing genomics research often do not have the incentives to do replication and other research required to verify the reliability of markers. The misalignment of incentives in the breeding supply chain can curtail the development of the projected advances in food production by genomics research. Using a sample of 24 genomic journals, we found more highly ranked journals tend to favor new research on identifying new QTL over replication research on previously identified QTL. Given that breeders will tend to adopt only those markers perceived to be reliable, the implicit lack of incentives for basic and applied genomic scientists to undertake replication research can impede agricultural innovation

Plant breeding for increased sustainability: challenges, opportunities and progress

Humanity is facing enormous challenges in the years to come: sustainability of agriculture and sustainability of our supply with food, feed and renewable materials are neither granted nor free. Especially, but not only, in the Global South, a sustainable increase in agricultural productivity and a steady reduction of avoidable losses are undoubtedly key issues that need to be addressed. In order to pinpoint the most pressing challenges and strategies to achieve targets, the United Nations have formulated the Sustainable Development Goals (https://sdgs. un.org/goals). Among these, several are directly or indirectly addressing agriculture, food supply and sustainability, most notably SDG2 (zero hunger), SDG12 (responsible consumption and production), SDG13 (climate action) and SDG15 (life on land)

AllInOne Pre-processing: A comprehensive preprocessing framework in plant field phenotyping

AllInOne Pre-processing is an innovative open-source, R-Shiny user interface package designed to facilitate the swift and effective preprocessing of plant phenotypic data. AllInOne Pre-processing incorporates a variety of statistical methods for data preprocessing, including: identifying missing patterns, imputing missing data using various imputation methods, visualizing data (box, violin, density, and scatter plot), detecting and amending outliers using quantile and Cook’s distance methods, estimating correlations, normalizing the data, estimating heritability, conducting spatial analysis, and calculating best linear unbiased prediction (BLUP) and estimator (BLUE). In general, AllInOne Pre-processing streamlines the preprocessing of phenotypic data, enabling users who lack programming knowledge to swiftly and accurately prepare their data for further analyses

Using Soybean Pedigrees to Identify Genomic Selection Signatures Associated with Long-Term Breeding for Cultivar Improvement

Genetic hitchhiking uncovers selection signatures related to traits of agronomic importance in crops. It has been primarily used at the level of domestication by comparing groups of wild germplasm to landraces or elite breeding lines. In this study, we compared two groups of cultivars defined by an elite Canadian soybean cultivar, OAC Bayfield, to identify selection signatures related to long-term breeding within a specific region. Cultivars were assigned to either a pre- or post-OAC Bayfield group. Of the 162 simple sequence repeat (SSR) markers used to genotype members of the pedigree, 14 were fixed and 19 exhibited a selective signature. An in silico analysis comparing our results to quantitative trait loci (QTL) reported in SoyBase showed that 18 out of the 19 markers with a selective signature were associated with at least one QTL. From the 80 QTL associated with the 18 markers, half were related to plant architecture, yield or maturity. In addition, the number and type of QTL associated with the fixed versus selected loci differed particularly, for yield. Genomic regions exhibiting a selection signature may contain important loci that either need to be conserved for agronomic performance or be targeted for introgressive breeding and germplasm enrichment.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Functional characterization of Cinnamate 4-hydroxylase gene family in soybean (Glycine max).

Cinnamate 4-hydroxylase (C4H) is the first key cytochrome P450 monooxygenase (P450) enzyme in the phenylpropanoid pathway. It belongs to the CYP73 family of P450 superfamily, and catalyzes the conversion of trans-cinnamic acid to p-coumaric acid. Since p-coumaric acid serves as the precursor for the synthesis of a wide variety of metabolites involved in plant development and stress resistance, alteration in the expression of soybean C4H genes is expected to affect the downstream metabolite levels, and its ability to respond to stress. In this study, we identified four C4H genes in the soybean genome that are distributed into both class I and class II CYP73 family. GmC4H2, GmC4H14 and GmC4H20 displayed tissue- and developmental stage-specific gene expression patterns with their transcript accumulation at the highest level in root tissues. GmC4H10 appears to be a pseudogene as its transcript was not detected in any soybean tissues. Furthermore, protein homology modelling revealed substrate docking only for GmC4H2, GmC4H14 and GmC4H20. To demonstrate the function of GmC4Hs, we modified a cloning vector for the heterologous expression of P450s in yeast, and used it for microsomal protein production and enzyme assay. Our results confirmed that GmC4H2, GmC4H14 and GmC4H20 contain the ability to hydroxylate trans-cinnamic acid with varying efficiencies

Experiment 1 data

This file contains all measurements and treatments for the first experiment in the study. Final root biomass is calculated by subtracting the weight of rocks from the initial measurement of root biomass. Cultivars a, b, and c, refer to OAC Wallace, OAC Calypso, and OAC Champion respectively. Any missing values refers to plants that died, did not germinate, or plant parts could not be retrieved because of damage

Data from: Identity recognition in response to different levels of genetic relatedness in commercial soya bean

Identity recognition systems allow plants to tailor competitive phenotypes in response to the genetic relatedness of neighbours. There is limited evidence for the existence of recognition systems in crop species and whether they operate at a level that would allow for identification of different degrees of relatedness. Here, we test the responses of commercial soya bean cultivars to neighbours of varying genetic relatedness consisting of other commercial cultivars (intraspecific), its wild progenitor Glycine soja, and another leguminous species Phaseolus vulgaris (interspecific). We found, for the first time to our knowledge, that a commercial soya bean cultivar, OAC Wallace, showed identity recognition responses to neighbours at different levels of genetic relatedness. OAC Wallace showed no response when grown with other commercial soya bean cultivars (intra-specific neighbours), showed increased allocation to leaves compared with stems with wild soya beans (highly related wild progenitor species), and increased allocation to leaves compared with stems and roots with white beans (interspecific neighbours). Wild soya bean also responded to identity recognition but these responses involved changes in biomass allocation towards stems instead of leaves suggesting that identity recognition responses are species-specific and consistent with the ecology of the species. In conclusion, elucidating identity recognition in crops may provide further knowledge into mechanisms of crop competition and the relationship between crop density and yield