XXXVI CICLO | Libro Pietro

My research interests lie at the intersection of cloud computing and genomics, specifically in the development of robust bioinformatics tools for RNA sequencing (RNA-seq) analysis. I am intrigued by the challenges posed by non-model organisms in genomics and aim to leverage my expertise in cloud architecture and software design to create scalable and adaptable solutions for genomic data analysis. My goal is to contribute to the field by developing efficient tools that can handle the complexities of de novo transcriptomic data, aiding in the understanding of genomic diversity and supporting biodiversity conservation efforts. I am particularly interested in how cloud-based technologies can be optimized for handling large-scale genomic datasets and in exploring how these technologies can enhance our understanding of molecular interactions and genetic expression in various species.

In genomics, RNA sequencing (RNA-seq) has revolutionized the analysis of gene expression. Although commonly used in model organisms, a huge amount of RNA-seq data is produced from non-model species that provide unique genetic information useful for biodiversity conservation. The development of robust bioinformatics tools for RNA-seq analysis of non-model organisms is critical to the study of genomic diversity. Non-model organisms lack well-annotated genomes and require specialized bioinformatic tools for accurate analysis. These tools must adapt to the study of different species and satisfy different research objectives (e.g. evolutionary behavioral studies). The de  novo transcriptomic resources developed in this thesis work constitute a knowledge base of the proxy catalog of protein coding genes for the analyzed species. The same resources can serve as a reference for further studies on genes differentially expressed in different experimental conditions. This research project promises to reveal genetic secrets, illuminate molecular interactions, and enrich our understanding of the diversity of life.

• Libro, P., Chiocchio, A., De Rysky, E., Di Martino, J., Bisconti, R., Castrignanò, T., & Canestrelli, D. (2023). De novo transcriptome assembly and annotation for gene discovery in Salamandra salamandra at the larval stage. Scientific Data, 10(1). https://doi.org/10.1038/s41597-023-02217-9

• Chiocchio, A., Libro, P., Martino, G., Bisconti, R., Castrignanò, T., & Canestrelli, D. (2022). Brain de novo transcriptome assembly of a toad species showing polymorphic anti-predatory behavior. Scientific Data, 9(1). 

   

• Libro, P., Bisconti, R., Chiocchio, A., Spadavecchia, G., Castrignanò, T., & Canestrelli, D. (2022). First brain de novo transcriptome of the Tyrrhenian tree frog, Hyla sarda, for the study of dispersal behavior. Frontiers in Ecology and Evolution, 10.

   

• Palomba, M., Libro, P., Di Martino, J., Rughetti, A., Santoro, M., Mattiucci, S., & Castrignanò, T. (2022). De novo transcriptome assembly and annotation of the third stage larvae of the zoonotic parasite Anisakis pegreffii. BMC Research Notes, 15(1). 

   

• D’Antonio, M., Libro, P., Picardi, E., Pesole, G., & Castrignanò, T. (2021). RAP: a web tool for RNA-Seq data analysis. In Methods in molecular biology (pp. 393–415). 

   

• Lo Giudice, C., Mansi, L., Flati, T., Gioiosa, S., Chillemi, G., Libro, P., Castrignanò, T., Pesole, G., & Picardi, E. (2021). RNA editing detection in HPC infrastructures. In Methods in molecular biology (pp. 253–270). 

• Palomba, M., Libro, P., Di Martino, J., Roca‐Geronès, X., Macali, A., Castrignanò, T., Canestrelli, D., & Mattiucci, S. (2023). De novo transcriptome assembly of an Antarctic nematode for the study of thermal adaptation in marine parasites. Scientific Data, 10(1).