In My Research Projects

This project explored the genetic basis of complex traits in Arabidopsis lyrata, by integrating transcriptome and phenotypic data from 800 natural and hybrid individuals. Using Bayesian mixed models (brms) and machine learning approaches (PCA, gradient boosting classifiers, Random Forests), we quantified additive and dominance variance components of 26,000 expressed genes and predicted those of fitness-related traits. The work combined modern whole genome and RNA-seq data, reproducible multi- pipelines (R, Python, Bash) on High-Performance Computing (HPC) systems (SLURM), with classical quantitative genetics and population genetics, to provide insights into trait heritability and breeding value optimization at both phenotypic and molecular scales.

It is intriguing to understand a key tension: not all functionally important variation translates into evolutionary capacity.

This research examined the role of seed dormancy in local adaptation - a key life-history strategy aligning germination with climate. We analysed natural variation of heat-induced secondary dormancy within 361 Arabidopsis thaliana accessions from across Europe. Using species distribution models, we predicted the resilience to future climate changes among genotypes with high and weak secondary dormancy. Additionally, we performed variant calling on whole genome data and used GWAS to identify genomic regions controlling secondary dormancy levels. The study advanced our understanding on complex adaptive mechanism and plant survival in harsh conditions.

It was fascinating how secondary dormancy contributes to local adaptation today and may buffer populations against future climate extremes.

Publication: https://onlinelibrary.wiley.com/doi/10.1111/mec.70086 

This project elucidated the interactions of the belowground herbivores, as we postulated that they can reciprocally influence each other via systemically induced plant responses. To test this hypothesis, we analyzed the performance of cabbage root fly (Delia radicum) larvae feeding on the main roots of field mustard (Brassica rapa) plants whose fine roots were infected by the root-knot nematode (Meloidogyne incognita). We monitored transcript upregulation (RT-qPCR) and the accumulation of the defense-related phytohormone and glucosinolates (HPLC, LC-MS).

It was fascinating to solve this "riddle in the dark" and provide evidence of plant-mediated interactions between belowground organisms. 

Publication: https:// doi.org/10.1093/plphys/kiaf109 

This study characterised a novel Arabidopsis transcription factor KUODA1 (KUA1) which has been identified as transcriptional repressor, regulating leaf cell expansion via reactive-oxygen-species homeostasis. Here we studied the activity of five KUA transcription factors and their dependence on TOPLESS/TOPLESS-RELATED (TPL/TPR) co-repressors in Arabidopsis thaliana. Using electrophoretic mobility shift assay (EMSA), DAP-seq, and molecular cloning, we studied how the KUAs recognized and bound to the DNA motif obtained from an endogenous target promoter. 

It was motivating to find out more about this novel transcription factor, as organ size regulation is of fundamental importance in plant development.