Probabilistic modeling of the evolution of gene synteny within reconciled phylogenies

Comparative Methods for Reconstructing Ancient Genome Organization

Comparative genomics considers the detection of similarities and differences between extant genomes, and, based on more or less formalized hypotheses regarding the involved evolutionary processes, inferring ancestral states explaining the similarities and an evolutionary history explaining the differences. In this chapter, we focus on the reconstruction of the organization of ancient genomes into chromosomes. We review different methodological approaches and software, applied to a wide range of datasets from different kingdoms of life and at different evolutionary depths. We discuss relations with genome assembly, and potential approaches to validate computational predictions on ancient genomes that are almost always only accessible through these predictions.

Transcriptologs: A Transcriptome-Based Approach to Predict Orthology Relationships

The detection of orthologs is a key approach in genomics, useful to understand gene evolution and phylogenetic relationships and essential for gene function prediction. However, a reliable annotation of the encoded protein regions is still a limiting aspect in genomics, mainly due to the lack of confirmatory experimental evidence at proteome level. Nevertheless, the current ortholog collections are generally based on protein sequence comparisons, in addition to the availability of large transcriptome sequence collections. We developed Transcriptologs, a method for the prediction of orthologs based on similarities of translated fragments from messenger RNAs of 2 species. We implemented a procedure to extend BLAST-based alignments and to define orthologs based on the Bidirectional Best Hit approach. Results from a test case on Arabidopsis thaliana and Sorghum bicolor transcript collections revealed in some cases outperformance of Transcriptologs in comparison with a classical protein-based analysis in terms of alignment quality, revealing similarities otherwise not detectable.