Phylogenomics: hace diez años!!

Vol. 8, Issue 3, 163-167, March 1998

INSIGHT/OUTLOOK
Phylogenomics: Improving Functional Predictions for Uncharacterized Genes by Evolutionary Analysis
Jonathan A. Eisen¹
Genome Research -- Eisen 8 (3): 163

The ability to accurately predict gene function based on gene sequence is an important tool in many areas of biological research. Such predictions have become particularly important in the genomics age in which numerous gene sequences are generated with little or no accompanying experimentally determined functional information. Almost all functional prediction methods rely on the identification, characterization, and quantification of sequence similarity between the gene of interest and genes for which functional information is available. Because sequence is the prime determining factor of function, sequence similarity is taken to imply similarity of function. There is no doubt that this assumption is valid in most cases. However, sequence similarity does not ensure identical functions, and it is common for groups of genes that are similar in sequence to have diverse (although usually related) functions. Therefore, the identification of sequence similarity is frequently not enough to assign a predicted function to an uncharacterized gene; one must have a method of choosing among similar genes with different functions. In such cases, most functional prediction methods assign likely functions by quantifying the levels of similarity among genes. I suggest that functional predictions can be greatly improved by focusing on how the genes became similar in sequence (i.e., evolution) rather than on the sequence similarity itself. It is well established that many aspects of comparative biology can benefit from evolutionary studies (Felsenstein 1985), and comparative molecular biology is no exception (e.g., Altschul et al. 1989; Goldman et al. 1996). In this commentary, I discuss the use of evolutionary information in the prediction of gene function. To appreciate the potential of a phylogenomic approach to the prediction of gene function, it is necessary to first discuss how gene sequence is commonly used to predict gene function and some general features about gene evolution.

Botany: Growing flowers

T . Barkman , M . Bendiksby , S . Lim , K . Salleh , J . Nais , D . Madulid , T . Schumacher. 2008. Accelerated Rates of Floral Evolution at the Upper Size Limit for Flowers. Current Biology 18: 1508 - 1513.

The world's largest flowers, of the Southeast Asian Rafflesia genus, which mimic the smell and appearance of rotting flesh, evolved much more quickly and more often than botanists expected.

Todd Barkman of Western Michigan University in Kalamazoo and his team hypothesized that it would have taken a long time for the Rafflesia flowers to evolve from their smaller ancestors to their current maximum size of one metre in diameter because of the many structural and physiological changes required to support such large flowers. To their surprise, they found that the flowers of some Rafflesia species have more or less doubled in size during the past one million to two million years. As Barkman points out, it is hard to imagine a giraffe doubling the length of its neck in the same time frame. The scientists suggest that even bigger flowers could evolve in future.

Fuente de la información: Research Highlights, Nature 455, 1010 (23 October 2008) | doi:10.1038/4551010a; Published online 22 October 2008.

Bosque: integrated phylogenetic analysis software

Ramírez-Flandes S. & O. Ulloa (2008).
Bosque: Integrated phylogenetic analysis software.
Bioinformatics 24(21):2539-2541;
doi: 10.1093/bioinformatics/btn466

Summary:
Phylogenetic analyses today involve dealing with computer files in different formats and often several computer programs. Although some widely used applications have integrated important functionalities for such analyses, they still work with local resources only: input/output files (users have to manage them) and local computing (users have sometimes to leave their programs, on their desktop computers, running for extended periods of time). To address these problems we have developed ‘Bosque’, a multi-platform client–server software that performs standard phylogenetic tasks either locally or remotely on servers, and integrates the results on a local relational database. Bosque performs sequence alignments and graphical visualization and editing of trees, thus providing a powerful environment that integrates all the steps of phylogenetic analyses.

Availability: http://bosque.udec.cl

Contact: sram@profc.udec.cl