2024/10/01 by Felix Langschied, Nicola Bordin, Salvatore Cosentino +16 · 1 voice
Biochemistry, Genetics and Molecular Biology · Chemistry · #Genomics and Phylogenetic Studies #Machine Learning in Bioinformatics #Advanced Proteomics Techniques and Applications
paper · pdf · doi:10.1093/gbe/evae224
openalex publication_date 2024/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
The era of biodiversity genomics is characterized by large-scale genome sequencing efforts that aim to represent each living taxon with an assembled genome. Generating knowledge from this wealth of data has not kept up with this pace. We here discuss major challenges to integrating these novel genomes into a comprehensive functional and evolutionary network spanning the tree of life. In summary, the expanding datasets create a need for scalable gene annotation methods. To trace gene function across species, new methods must seek to increase the resolution of ortholog analyses, e.g. by extending analyses to the protein domain level and by accounting for alternative splicing. Additionally, the scope of orthology prediction should be pushed beyond well-investigated proteomes. This demands the development of specialized methods for the identification of orthologs to short proteins and noncoding RNAs and for the functional characterization of novel gene families. Furthermore, protein structures predicted by machine learning are now readily available, but this new information is yet to be integrated with orthology-based analyses. Finally, an increasing focus should be placed on making orthology assignments adhere to the findable, accessible, interoperable, and reusable (FAIR) principles. This fosters green bioinformatics by avoiding redundant computations and helps integrating diverse scientific communities sharing the need for comparative genetics and genomics information. It should also help with communicating orthology-related concepts in a format that is accessible to the public, to counteract existing misinformation about evolution.