Genome-wide association study and network analysis of in vitro transformation in Populus trichocarpa support key roles of diverse phytohormone pathways and cross talk.
Michael F NagleJialin YuanDamanpreet KaurCathleen MaEkaterina PeremyslovaYuan JiangGreg S GoralogiaAnna MagnusonJia Yi LiWellington MucheroFuxin LiSteven H StraussPublished in: The New phytologist (2024)
Wide variation in amenability to transformation and regeneration (TR) among many plant species and genotypes presents a challenge to the use of genetic engineering in research and breeding. To help understand the causes of this variation, we performed association mapping and network analysis using a population of 1204 wild trees of Populus trichocarpa (black cottonwood). To enable precise and high-throughput phenotyping of callus and shoot TR, we developed a computer vision system that cross-referenced complementary red, green, and blue (RGB) and fluorescent-hyperspectral images. We performed association mapping using single-marker and combined variant methods, followed by statistical tests for epistasis and integration of published multi-omic datasets to identify likely regulatory hubs. We report 409 candidate genes implicated by associations within 5 kb of coding sequences, and epistasis tests implicated 81 of these candidate genes as regulators of one another. Gene ontology terms related to protein-protein interactions and transcriptional regulation are overrepresented, among others. In addition to auxin and cytokinin pathways long established as critical to TR, our results highlight the importance of stress and wounding pathways. Potential regulatory hubs of signaling within and across these pathways include GROWTH REGULATORY FACTOR 1 (GRF1), PHOSPHATIDYLINOSITOL 4-KINASE β1 (PI-4Kβ1), and OBF-BINDING PROTEIN 1 (OBP1).
Keyphrases
- high throughput
- network analysis
- transcription factor
- genome wide association study
- binding protein
- high resolution
- deep learning
- stem cells
- genome wide
- copy number
- optical coherence tomography
- high density
- randomized controlled trial
- tyrosine kinase
- machine learning
- dna methylation
- living cells
- wound healing
- genome wide identification
- stress induced
- arabidopsis thaliana