The Evolutionary Genomics group, led by Mar Albà, uses comparative genomics and large-scale data analysis to understand the complexity of gene regulation and evolutionary innovation. The group develops bioinformatics pipelines to analyze large amounts of genomics data. We use novel approaches to reconstruct and quantify the transcriptome using high-throughput RNA sequencing data, including long-read technologies such as Nanopore. We are also using techniques for sequencing ribosome-protected RNA fragments, also known as ribosome profiling. Using these techniques we have been able to discover many novel translated small ORFs (sORFs). Some of these sORFs correspond to highly conserved small proteins, or micropeptides, that can have important cellular functions. Others are intermediates in the process of generation of de novo genes, new types of gene that arise from previously non-coding parts of the genome. We are also interested in using transcriptomics data to study adaptation to extreme conditions, such as hibernation in mammals. In this regard, we have recently characterized the molecular mechanisms associated with the induction of torpor in hibernating species of lemurs, which may lead to future applications in human medicine.