Identification of potential Auxin Response Candidate genes for soybean rapid canopy coverage through comparative evolution and expression analysis.
Deisiany F NeresJoseph S TaylorJohn A BryantBastiaan O R BargmannR Clay WrightPublished in: bioRxiv : the preprint server for biology (2023)
Glycine max , soybean, is an abundantly cultivated crop worldwide. Efforts have been made over the past decades to improve soybean production in traditional and organic agriculture, driven by growing demand for soybean-based products. Rapid canopy cover development (RCC) increases soybean yields and suppresses early-season weeds. Genome-wide association studies have found natural variants associated with RCC, however causal mechanisms are unclear. Auxin modulates plant growth and development and has been implicated in RCC traits. Therefore, modulation of auxin regulatory genes may enhance RCC. Here, we focus on the use of genomic tools and existing datasets to identify auxin signaling pathway RCC candidate genes, using a comparative phylogenetics and expression analysis approach. We identified genes encoding 14 TIR1/AFB auxin receptors, 61 Aux/IAA auxin co-receptors and transcriptional co-repressors, and 55 ARF auxin response factors in the soybean genome. We used Bayesian phylogenetic inference to identify soybean orthologs of Arabidopsis thaliana genes, and defined an ortholog naming system for these genes. To further define potential auxin signaling candidate genes for RCC, we examined tissue-level expression of these genes in existing datasets and identified highly expressed auxin signaling genes in apical tissues early in development. We identified at least 4 TIR1/AFB , 8 Aux/IAA , and 8 ARF genes with highly specific expression in one or more RCC-associated tissues. We hypothesize that modulating the function of these genes through gene editing or traditional breeding will have the highest likelihood of affecting RCC while minimizing pleiotropic effects.
Keyphrases
- arabidopsis thaliana
- genome wide
- genome wide identification
- bioinformatics analysis
- renal cell carcinoma
- signaling pathway
- transcription factor
- gene expression
- dna methylation
- poor prognosis
- healthcare
- climate change
- epithelial mesenchymal transition
- binding protein
- quality improvement
- single cell
- genome wide association
- quantum dots
- endoplasmic reticulum stress