Researchers from the University of Barcelona (UB), the Institute of Biomedicine of the University of Barcelona (IBUB) –bases in the PCB– and the Centre for Genomic Regulation (CRG) participate in an international consortium of scientists that has published a systematic assessment of the software used to analyse gene expression departing from the data obtained by the sequencing method RNA-seq. Results, published recently on the journal Nature Methods (doi:10.1038/nmeth.2714), may inspire new computing approaches to handle current and future technologies for gene expression analysis.

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Experts Josep F. Abril, from the Department of Genetics of the UB and research at IBUB, and Roderic Guigó, from CRG, collaborate in the research; they were the only Spanish experts who participated in the Human Genome Project, a really important milestone in the field of human genetics.

Scientists use the method of RNA sequencing to see how genes are being expressed across an entire genome. But how can they analyse this information? Is the software they use good enough to do so? In the research, the consortium RNA-seq Genome Annotation Assessment (RGASP), an initiative affiliated with the project ENCODE (ENCyclopedia Of DNA Elements), evaluated the performance of a wide range of RNA-seq computer programs. Experts were able to specify which approaches work well for certain tasks, and which areas can be improved.

“The article results from a project aimed at assessing the reliability of the most modern gene prediction software, in the context of the evidences provided by RNA-seq data, and how these data could improve gene annotation and the computational tools that define them”, explains Josep F. Abril, researcher at the Computational Genomics Lab of the UB i member of the IBUB.

By systematically comparing the existing computational tools for gene prediction we try to determine whether the new RNA-seq data improve or not the reliability of genetic predictions”, explains Josep F. Abril, director of the Computational Genomics Lab of the UB. “Apart from providing excellent new tools for gene prediction —he adds—, we have also identified the questions we should address in the future”.

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