Prof Dr Agnieszka Golicz (PI)
I am a bioinformatician and a Group Leader at the Justus Liebig University Giessen. I completed a BSc (Hons) in Molecular Genetics at the University of Dundee, a PhD in Applied Bioinformatics at the University of Queensland and a McKenzie Fellowship funded post-doctoral research at the University of Melbourne. I have led and contributed to diverse genomics and pangenomics projects, studying eukaryotic (mostly plant) genomic and transcriptomic diversity. In 2020 I was awarded the Sofja Kovalevskaja Award from the Humboldt Foundation to start a new group in Germany.
Dr Silvia Zanini (Post-doctoral researcher)
My main research interest is the elucidation of non-coding sequences’ role in crop trait variations, from disease resistance to plant development and yield. My current project focuses on annotating the regulatory landscape and assessing chromatin architectures in the polyploid crop Brassica napus (oilseed rape). In particular, I am responsible for the generation and analysis of high-throughput data obtained from both vegetative and reproductive tissues, including ATAC-Seq, Hi-C and RNA-Seq. These data will enable us to accurately map cis-regulatory elements (CREs) and understand the non-linear organization of rapeseed genome. Afterwards, these datasets will be integrated with the genomic data analysed by the other members of the group to generate a comprehensive rapeseed cis-regulatory atlas, facilitating the study of both coding and regulatory variants and their effect on physiological, developmental and metabolic traits.
Ms Gözde Yildiz (PhD candidate)
My project focuses on analysing Brassica napus (oilseed rape) sequencing data to identify genomic variations and especially structural variants (SVs). I am interested in developing hybrid methods utilizing both short read (Illumina) and long read (Oxford Nanopore) sequencing for accurate variant discovery and genotyping. Ultimately, I aim to understand the impact of structural variants on gene expression and regulatory regions linking the differences observed to plant physiology and morphology. My current focus is benchmarking of different SV discovery methods using both linear genome sequences and pangenome graphs.
Mr José Antonio Montero Tena (PhD candidate)
My PhD project aims to define the recombination landscape in Brassica napus (oilseed rape) by identifying genetic, genomic or epigenomic patterns associated with the position and frequency of genetic exchange events that take place during meiosis. The knowledge obtained for this widespread crop could provide breeders with tools to generate genetic diversity in rapeseed. This could be extremely important since climate change urges the development of new crop varieties that are able cope with challenging environmental conditions. My focus lies on bioinformatics applied to genome analysis. I am proficient in R and currently I am learning python and bash in order to write code that can help me achieve my research goals. I also have strong interest in sequencing and I would like to learn more about next-generation sequencing data analysis.
Mr Kevin Rockenbach (PhD candidate)
My project focuses on the development of deep learning models for gene expression prediction from genomic sequence, aiming to predict both the overall levels and tissue specific patterns of expression. We want to understand the extent to which promotors can be used for expression prediction, giving insights into the regulatory architecture of Brassica napus genome. Our estimates of gene expression may help identify genes of interest for further investigation. We also plan to use our models to predict the impact of structural variation on gene expression.
Ms Kübra Arslan (PhD candidate)
My Ph.D. project aims to generate a pan-genome graph representing genomic diversity of faba bean. Due to the extremely large faba bean genome size, its complexity and repeat content I will be evaluating several possible strategies and methodologies. One of the key aspects of this project will be better understating of the extent of gene and repeat content variation within the faba bean germplasm used in modern breeding programs. I am fascinated by the future of interesting genomes and what they may reveal.
Mr Venkataramana Kopalli
My PhD project aims to assemble a detailed graphical pangenome for Sorghum bicolor breeding material to identify and catalogue genome-wide gene presence-absence variants and unterstand link between structural variation and traits. I am currently focusing on benchmarking the available tools and pipelines for pangenome and pangenome graph construction. This will be followed by assembling of a detailed graphical pangenome for elite Sorghum bicolor, which we plan to use to understand the occurrence of heterosis and cold tolerance in Sorghum.
Mr Rishi Srivastava
My doctoral research project is at the intersection of cutting-edge deep learning and genomics. Here, we are developing deep learning models to predict the effect of genomic variations on gene expression. The study encompasses various types of genomic variations, including SNPs, InDels, structural variations, and more. Concurrently, I am also serving as a Data Manager for the IRTG-funded Accelerating Crop Genetic Gain (ACGG) program, where my responsibilities involve creating a database to effectively manage all the data generated within this initiative. My strong passion lies in the realms of programming and machine learning.
Agricultural Bioinformatics Lab 