Dr. Gabriela Aguileta

Bioinformatics and Integrative Genomics

Research Interests

I use statistics and bioinformatics to study evolutionary and biomedical questions. My studies range from the molecular level of sequence evolution, under the framework of comparative, biomedical and integrative genomics, up to the level of ecology, metabolic regulation, and cancer. I am interested in the integration of different data types issuing from epigenetics and metabolomics to study the transcriptional regulation of metabolic processes. I also work on data analysis in cancer genomics, to assess the quality of WGS and bioinformatics pipelines for variant calling of somatic and germline variants.

I have developed, designed and collaborated in several research projects. Here are the main areas of my research so far:

Integrative genomics

Integrating RNA-, ChIP-seq and metabolomics data to understand the link between obesity, metabolic disorders and inflammation
Development of bioinformatics and statistical approaches for the multi-dimensional integration of different types of data in the context of metabolic regulation

Comparative genomics

Genomic rearrangements and the rapid evolution of specific gene families promote pathogenicity
The role of transposable elements and repeats on mitochondrial genome rearrangements
The evolution of the bacterial ribosomal protein network using statistical classifiers and random forest methods

Cancer genomics

Benchmarking and data analysis of WGS methods and bioinformatics pipelines for somatic variant calling
Data analysis for periodic Interlaboratory Comparisons to assess the quality of WGS for germline variant calling

Ecological genomics

Hybridization, host jumps and reproductive mode leading to pathogen specialization and eventually to speciation
Ancestral trans-specific polymorphism at fungal mating types. Evolution of sexual chromosomes in fungi

Phylogenomics

Development of a phylogenomics approach to identify the most informative genes to build a robust phylogeny across the fungal kingdom
FUNYBASE database for fungal phylogenomics, a comprehensive tool for the use of single-copy orthologs for phylogenetic reconstruction across the main fungal groups
Use of FUNYBASE and optimized markers for the identification of cryptic fungal species. Barcoding fungal species used in cheese production
Development of Phylo-MCOA: a method based on multiple co-inertia analysis for the identification of outlier genes and species in phylogenomic studies

Molecular Evolution

Identification of rapidly-evolving genes involved in fungal pathogenicity, host specialization and potentially speciation
Evolution of gene families by gene duplication and functional divergence identified by measuring variable selective pressure acting on protein-coding genes
Molecular dating and ancestral state reconstruction in vertebrates