Biology subjects

Hodel, M.

Publications and source records attributed to Hodel, M..

4 recordsLinked to original sources

bioRxiv2024

Evaluation of genomic and phenomic prediction for application in apple breeding

Apple breeding schemes can be improved by using genomic prediction models to forecast the performance of breeding material. These models predictive ability depends on factors like trait genetic architecture, training set size, relatedness of the selected material to the training set, and the validation method used. Alternative genotyping methods such as RADseq and complementary data from near-infrared spectroscopy could help improve the cost-effectiveness of genomic selection. However, the impact of these factors and alternative approaches on predictive ability beyond experimental populations still need to be investigated. In this study, we evaluated 137 prediction scenarios varying the described factors and alternative approaches, offering recommendations for implementing genomic selection in apple breeding. Our results show that extending the training set with germplasm related to the predicted breeding material can improve average predictive ability across eleven studied traits by up to 0.08. The study emphasizes the usefulness of leave-one-family-out validation, reflecting the application of genomic selection to a new family, although it reduced average predictive ability across traits by up to 0.24 compared to cross-validation. Similar average predictive abilities across traits indicate that imputed RADseq data could be a suitable genotyping alternative to SNP array datasets. The best-performing scenario using near-infrared spectroscopy data for phenomic prediction showed a 0.35 decrease in average predictive ability across traits compared to conventional genomic prediction, suggesting that the tested phenomic selection approach is impractical. These findings offer valuable guidance for applying genomic selection in apple breeding, ultimately leading to the development of breeding material with improved quality.

genomics↗

bioRxiv2023

The genetic basis of apple shape and size unraveled by digital phenotyping

Great diversity of shape, size, and skin color is observed among the fruits of different apple genotypes. These traits are critical for consumers and therefore interesting targets for breeding new apple varieties. However, they are difficult to phenotype and their genetic basis, especially for fruit shape and ground color, is largely unknown. We used the fruit FruitPhenoBox to digitally phenotype 506 genotypes of the apple reference population (apple REFPOP) genotyped for 303,148 single nucleotide polymorphism (SNP) markers. From the apple images, 573 highly heritable features describing fruit shape and size as well as 17 highly heritable features for fruit skin color were extracted to explore genotype-phenotype relationships. Out of these features, nine and four principal components (PCs) as well as 16 and eight uncorrelated features were chosen to carry out genome-wide association studies for fruit shape, size, and fruit skin color, respectively. In total, 69 SNPs scattered over all 17 apple chromosomes were significantly associated with round, conical, cylindrical, or symmetric fruit shapes and fruit size. Novel associations with major effect on round or conical fruit shapes and fruit size were identified on chromosomes 1 and 2. Additionally, 16 SNPs associated with PCs and uncorrelated features related to red over color as well as green and yellow ground color were found on eight chromosomes. The identified associations can be used to advance marker-assisted selection in apple fruit breeding to systematically select for desired fruit appearance.

plant biology↗

bioRxiv2018

Genetic determination of stomatal patterning in winter wheat (Triticum aestivum L.)

Leaf stomata are microscopic pores mediating plant-environment interactions. Their role in carbon uptake and transpiration make them prime candidates for improving water use efficiency (WUE). Stomatal density (SD), the number of stomata per unit area, has been shown to be negatively correlated with WUE. However, little is known about the genetic basis of SD in wheat (Triticum aestivum L.), and to what extant genetic variation exists in contemporary wheat germplasm. Here, we evaluated stomatal patterning over two growing seasons in a set of 333 wheat lines, representing the European winter wheat germplasm. Stomatal patterning was mainly determined by two underlying traits, the distance between files of stomata and the distance between stomata within a file. By haplotype association mapping, quantitative trait loci for SD were consistently detected in both seasons on wheat chromosomes (CHR) 2A, 3A and 7B. The single nucleotide polymorphism markers most significantly associated with SD coincided with the genes INDUCER OF CBF EXPRESSION 1 (ICE1) and STOMATAL CYTOKINESIS-DEFECTIVE 1 (SCD1) on CHR 3A, and genes involved in ethylene and auxin signaling on CHR 2A and 7B, respectively. Our study unlocks the phenotypic and genotypic variation for stomatal patterning traits in contemporary wheat germplasm. It provides gene targets for functional validation and practical tools to manipulate SD using marker-assisted selection for crop improvement.

plant biology↗

bioRxiv2018

Self-regulation of the Dopaminergic Reward Circuit in Cocaine Users with Mental Imagery and Neurofeedback

Background: Enhanced drug-related reward sensitivity accompanied by impaired sensitivity to non-drug related rewards in the mesolimbic dopamine system are thought to underlie the broad motivational deficits and dysfunctional decision-making frequently observed in cocaine use disorder (CUD). Effective approaches to modify this imbalance and reinstate non-drug reward responsiveness are urgently needed. Here we examine whether cocaine users (CU) can use mental imagery of non-drug rewards to self-regulate the ventral tegmental area and substantia nigra (VTA/SN). We expected that compulsive and obsessive thoughts about cocaine consumption would hamper the ability to self-regulate the VTA/SN. Finally, we tested if self-regulation of the VTA/SN can be improved with real-time fMRI (rtfMRI) neurofeedback (NFB).\n\nMethods: Twenty-two CU and 28 healthy controls (HC) were asked to voluntarily up-regulate VTA/SN activity with rewarding non-drug imagery alone, or combined with rtfMRI NFB of VTA/SN activity. Obsessive-compulsive drug use was measured with the Obsessive Compulsive Cocaine Use Scale (OCCUS).\n\nResults: CU were able to induce activity in the dopaminergic midbrain and other reward regions with reward imagery. The ability to self-regulate the VTA/SN was reduced in those with more severe obsessive-compulsive drug use. NFB enhanced the effect of non-drug imagery.\n\nConclusion: CU can voluntary activate their reward system through non-drug related imagery and improve this ability with rtfMRI NFB. Combining reward imagery and rtFMRI NFB has great potential for modifying the maladapted reward sensitivity and reinstating non-drug reward responsiveness. This motivates further work to examine the therapeutic potential of cognitive neurostimulation in CUD.

neuroscience↗