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Lebron, R.

Publications and source records attributed to Lebron, R..

2 recordsLinked to original sources

Tracking evolutionary trends towards increasing complexity: a case study in Cyanobacteria

Progressive evolution, the tendency towards increasing complexity, is a controversial issue in Biology, whose resolution requires a proper measurement of complexity. Genomes are the best entities to address this challenge, as they record the history and information gaining of organisms in their ongoing biotic and environmental interactions. Using six metrics of genome complexity, none of which is primarily associated to biological function, we measure genome complexity in 91 genomes from the phylum Cyanobacteria. Several phylogenetic analyses reveal the existence of progressive evolution towards higher genome complexity: 1) all the metrics detect strong phylogenetic signals; 2) ridge regressions detect positive trends towards higher complexity; and 3) classical proofs for progressive evolution (the minimum, the ancestor-descendent and the sub-clade tests), show that some of these positive trends are driven, being mainly due to natural selection. These findings support the existence of progressive genome evolution in this ancient and diverse group of organisms.

evolutionary biology↗

miRNAgFree: prediction and profiling of novel microRNAs without genome assembly

The prediction of novel miRNA genes generally requires the availability of genome sequences in order to assess important properties such as the characteristic hairpin-shaped secondary structure. However, although the sequencing costs have decreased over the last years, still many important species lack an assembled genome of certain quality. We implemented an algorithm which for the first time exploits characteristic biogenesis features like the 5 homogeneity that can be assessed without genome sequences. We used a phylogenetically broad spectrum of well annotated animal genomes for benchmarking. We found that between 90-100% of the most expressed miRNA candidates (top quartile) corresponded to known miRNA sequences.

bioinformatics↗