Genomics of Gene Expression
The Genomics of Gene Expression Lab is interested in understanding the functional aspects of gene expression at the genome-wide level and it relationship with diseases and traits. For that we develop statistical methods and software tools that analyze the (dynamics aspects of) transcriptome data, integrate these with other types of molecular data and annotate them functionally, most recently making use of Next Generation Sequencing technologies. The current areas of research are:
- Patho-transcriptomics: genome architecture and gene expression regulation in pathogenic bacteria (Chlamydia and Pseudomonas) and fungi (Aspergillus and Fusarium).
- Genomics and epigenomics in Lupus Eritomatoso Sistémico.
- Epigenomic markers in neuroblastoma for diagnosis and prognosis.
- Systems Biology in the immune system and its association to leukemia.
- Functional role long-non coding RNA and their association to disease.
Functional genomics research is complemented with the development of bioinformatics software for the analysis of genomics data: Blast2GO (functional annotation), Paintomics (genomics visualization), Qualimap (QC of mapped NGS data), maSigPro and SEA (time series analysis), minAS and ASCA-genes (gene expression analysis), SEA and NOIseq (RNA-seq analysis).
The laboratory is currently coordinator of two FP7 research projects: STATegra, on the development of statistical tools for integration of heterogeneous omics datasets, and DEANN, a Marie Curie IRSES for developing a Europe-SouthAmerica NGS analysis network.
SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification.
Tardaguila M, de la Fuente L, Marti C, Pereira C, Pardo-Palacios FJ, Del Risco H, Ferrell M, Mellado M, Macchietto M, Verheggen K, Edelmann M, Ezkurdia I, Vazquez J, Tress M, Mortazavi A, Martens L, Rodriguez-Navarro S, Moreno-Manzano V, Conesa A
Genome research , 2018 Feb 9,
PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data
Hernandez-de-Diego R, Tarazona S, Martinez-Mira C, Balzano-Nogueira L, Furió-Tarí P, Pappas G, Conesa A.
Nucleic acids research , 2018 ,
spongeScan: A web for detecting microRNA binding elements in lncRNA sequences.
Furió-Tarí P, Tarazona S, Gabaldón T, Enright AJ, Conesa A
Nucleic acids research , 2016 May 19,
A survey of best practices for RNA-seq data analysis.
Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A, Szczesniak MW, Gaffney DJ, Elo LL, Zhang X, Mortazavi A
Genome biology , 2016 Jan 26, vol. 17, pag. 13
Differential expression in RNA-seq: a matter of depth.
Tarazona S, García-Alcalde F, Dopazo J, Ferrer A, Conesa A
Genome research , 2011 Dec, vol. 21, pag. 2213-23, Impact Factor: 13.608