A world-wide analysis of reduced sensitivity to DMI fungicides in the banana pathogen Pseudocercospora fijiensis.

BACKGROUND: Pseudocercospora fijiensis is the causal agent of the black leaf streak disease (BLSD) of banana. Bananas are important global export commodities and a major staple food. Their susceptibility to BLSD pushes disease management towards excessive fungicide use, largely relying on multisite inhibitors and sterol demethylation inhibitors (DMIs). These fungicides are ubiquitous in plant disease control, targeting the CYP51 enzyme. We examined sensitivity to DMIs in P. fijiensis field isolates collected from various major banana production zones in Colombia, Costa Rica, Dominican Republic, Ecuador, the Philippines, Guadalupe, Martinique and Cameroon and determined the underlying genetic reasons for the observed phenotypes. RESULTS: We observed a continuous range of sensitivity towards the DMI fungicides difenoconazole, epoxiconazole and propiconazole with clear cross-sensitivity. Sequence analyses of PfCYP51 in 266 isolates showed 28 independent amino acid substitutions, nine of which correlated with reduced sensitivity to DMIs. In addition to the mutations, we observed up to six insertions in the Pfcyp51 promoter. Such promoter insertions contain repeated elements with a palindromic core and correlate with the enhanced expression of Pfcyp51 and hence with reduced DMI sensitivity. Wild-type isolates from unsprayed bananas fields did not contain any promoter insertions. CONCLUSION: The presented data significantly contribute to understanding of the evolution and global distribution of DMI resistance mechanisms in P. fijiensis field populations and facilitate the prediction of different DMI efficacy. The overall reduced DMI sensitivity calls for the deployment of a wider range of solutions for sustainable control of this major banana disease. © 2021 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes.

Assessment of the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear-derived variation (the nucleotype). Haploid-inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)1. We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1,859 phenotypes under both stable and fluctuating conditions. We show that natural variation in the plasmotype results in both additive and epistatic effects across all phenotypic categories. Plasmotypes that induce more additive phenotypic changes also cause more epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average, epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multi-level nucleotype-plasmotype-environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation that is predominantly exposed under certain conditions. The production of cybrids using haploid inducers is a rapid and precise method for assessment of the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in these combinations and identify favourable combinations to enhance plant performance.

Dietary Intakes of Vegetable Protein, Folate, and Vitamins B-6 and B-12 Are Partially Correlated with Physical Functioning of Dutch Older Adults Using Copula Graphical Models.

BACKGROUND: In nutritional epidemiology, dealing with confounding and complex internutrient relations are major challenges. An often-used approach is dietary pattern analyses, such as principal component analysis, to deal with internutrient correlations, and to more closely resemble the true way nutrients are consumed. However, despite these improvements, these approaches still require subjective decisions in the preselection of food groups. Moreover, they do not make efficient use of multivariate dietary data, because they detect only marginal associations. We propose the use of copula graphical models (CGMs) to model and make statistical inferences regarding complex associations among variables in multivariate data, where associations between all variables can be learned simultaneously. OBJECTIVE: We aimed to reconstruct nutritional intake and physical functioning networks in Dutch older adults by applying a CGM. METHODS: We addressed this issue by uncovering the pairwise associations between variables while correcting for the effect of remaining variables. More specifically, we used a CGM to infer the precision matrix, which contains all the conditional independence relations between nodes in the graph. The nonzero elements of the precision matrix indicate the presence of a direct association. We applied this method to reconstruct nutrient-physical functioning networks from the combined data of 4 studies (Nu-Age, ProMuscle, ProMO, and V-Fit, total n = 662, mean ± SD age = 75 ± 7 y). The method was implemented in the R package nutriNetwork which is freely available at https://cran.r-project.org/web/packages/nutriNetwork. RESULTS: Greater intakes of vegetable protein and vitamin B-6 were partially correlated with higher scores on the total Short Physical Performance Battery (SPPB) and the chair rise test. Greater intakes of vitamin B-12 and folate were partially correlated with higher scores on the chair rise test and the total SPPB, respectively. CONCLUSIONS: We determined that vegetable protein, vitamin B-6, folate, and vitamin B-12 intakes are partially correlated with improved functional outcome measurements in Dutch older adults.

Identification of agronomically important QTL in tetraploid potato cultivars using a marker-trait association analysis.

Nineteen tuber quality traits in potato were phenotyped in 205 cultivars and 299 breeder clones. Association analysis using 3364 AFLP loci and 653 SSR-alleles identified QTL for these traits. Two association mapping panels were analysed for marker-trait associations to identify quantitative trait loci (QTL). The first panel comprised 205 historical and contemporary tetraploid potato cultivars that were phenotyped in field trials at two locations with two replicates (the academic panel). The second panel consisted of 299 potato cultivars and included recent breeds obtained from five Dutch potato breeding companies and reference cultivars (the industrial panel). Phenotypic data for the second panel were collected during subsequent clonal selection generations at the individual breeding companies. QTL were identified for 19 agro-morphological and quality traits. Two association mapping models were used: a baseline model without, and a more advanced model with correction for population structure and genetic relatedness. Correction for population structure and genetic relatedness was performed with a kinship matrix estimated from marker information. The detected QTL partly not only confirmed previous studies, e.g. for tuber shape and frying colour, but also new QTL were found like for after baking darkening and enzymatic browning. Pleiotropic effects could be discerned for several QTL.

Natural variation for seed longevity and seed dormancy are negatively correlated in Arabidopsis.

Dormancy is a state of metabolic arrest that facilitates the survival of organisms during environmental conditions incompatible with their regular course of life. Many organisms have deep dormant stages to promote an extended life span (increased longevity). In contrast, plants have seed dormancy and seed longevity described as two traits. Seed dormancy is defined as a temporary failure of a viable seed to germinate in conditions that favor germination, whereas seed longevity is defined as seed viability after dry storage (storability). In plants, the association of seed longevity with seed dormancy has not been studied in detail. This is surprising given the ecological, agronomical, and economic importance of seed longevity. We studied seed longevity to reveal its genetic regulators and its association with seed dormancy in Arabidopsis (Arabidopsis thaliana). Integrated quantitative trait locus analyses for seed longevity, in six recombinant inbred line populations, revealed five loci: Germination Ability After Storage1 (GAAS1) to GAAS5. GAAS loci colocated with seed dormancy loci, Delay Of Germination (DOG), earlier identified in the same six recombinant inbred line populations. Both GAAS loci and their colocation with DOG loci were validated by near isogenic lines. A negative correlation was observed, deep seed dormancy correlating with low seed longevity and vice versa. Detailed analysis on the collocating GAAS5 and DOG1 quantitative trait loci revealed that the DOG1-Cape Verde Islands allele both reduces seed longevity and increases seed dormancy. To our knowledge, this study is the first to report a negative correlation between seed longevity and seed dormancy.

Analysis of natural allelic variation in Arabidopsis using a multiparent recombinant inbred line population.

To exploit the diversity in Arabidopsis thaliana, eight founder accessions were crossed to produce six recombinant inbred line (RIL) subpopulations, together called an Arabidopsis multiparent RIL (AMPRIL) population. Founders were crossed pairwise to produce four F1 hybrids. These F1s were crossed according to a diallel scheme. The resulting offspring was then selfed for three generations. The F4 generation was genotyped with SNP and microsatellite markers. Data for flowering time and leaf morphology traits were determined in the F5 generation. Quantitative trait locus (QTL) analysis for these traits was performed using especially developed mixed-model methodology, allowing tests for QTL main effects, QTL by background interactions, and QTL by QTL interactions. Because RILs were genotyped in the F4 generation and phenotyped in the F5 generation, residual heterozygosity could be used to confirm and fine-map a number of the QTLs in the selfed progeny of lines containing such heterozygosity. The AMPRIL population is an attractive resource for the study of complex traits.

Natural variation for seed dormancy in Arabidopsis is regulated by additive genetic and molecular pathways.

Timing of germination is presumably under strong natural selection as it determines the environmental conditions in which a plant germinates and initiates its postembryonic life cycle. To investigate how seed dormancy is controlled, quantitative trait loci (QTL) analyses has been performed in six Arabidopsis thaliana recombinant inbred line populations by analyzing them simultaneously using a mixed model QTL approach. The recombinant inbred line populations were derived from crosses between the reference accession Landsberg erecta (Ler) and accessions from different world regions. In total, 11 delay of germination (DOG) QTL have been identified, and nine of them have been confirmed by near isogenic lines (NILs). The absence of strong epistatic interactions between the different DOG loci suggests that they affect dormancy mainly by distinct genetic pathways. This was confirmed by analyzing the transcriptome of freshly harvested dry seeds of five different DOG NILs. All five DOG NILs showed discernible and different expression patterns compared with the expression of their genetic background Ler. The genes identified in the different DOG NILs represent largely different gene ontology profiles. It is proposed that natural variation for seed dormancy in Arabidopsis is mainly controlled by different additive genetic and molecular pathways rather than epistatic interactions, indicating the involvement of several independent pathways.