Research Lab

Computational Multi-Omics

COMICS 20202
29685

Lab Members

Lab leader

Independent researcher

PhD student

Other members

Research Interests

Our mission is to understand the (epi)genome biology and its impact on cancer and other diseases using computational multi-omics approaches. Such methods rely on the statistical analysis and integration of large scale data (high-throughput sequencing, microarrays, proteomics, high-throughput screening) and clinical/phenotypic data.

Research Highlights
Transcription Dynamics Prevent RNA-Mediated Genomic Instability through SRPK2-Dependent DDX23 Phosphorylation

Genomic instability is frequently caused by nucleic acid structures termed R-loops that are formed during transcription. Despite their harmful potential, mechanisms that sense, signal, and suppress these structures remain elusive. We have showed that oscillations in RNA Pol II dynamics during transcription initiate a molecular pathway that prevents R-loops accumulation. Depletion of either SRPK2 or DDX23, as observed in adenoid cystic carcinoma, disrupts this pathway, leading to RNA-mediated genomic instability (Sridhara et al, Cell Reports, 2017).

 

fig1Transcription Dynamics Prevent RNAMediated Genomic Instability through SRPK2-Dependent DDX23 Phosphorylation

 

Introns Protect Eukaryotic Genomes from Transcription-Associated Genetic Instability

Transcription is a source of genetic instability that can notably result from the formation of genotoxic DNA:RNA hybrids, R-loops, between the nascent RNA and its template. By combining the genetic manipulation of intron content with genome-wide analyses in both yeasts and human cells, we revealed a function for introns in counteracting DNA:RNA hybrid (R-loop) formation and its deleterious impact on genetic stability (Bonnet et al, Mol Cell, 2017).

 

fig2Introns Protect Eukaryotic Genomes from Transcription-Associated Genetic Instability

 

Representative Projects

  • “Decoding pseudogene transcriptional regulation during cell differentiation” – FCT-MCTES, Total and Unit Funding: € 50,000. Ana Rita Grosso (PI)
  • “Targeting Intra-Tumor heterogeneity as a promising therapeutic strategy for cancer”, FCT-MTES, Total and Unit Funding € 239,478. Ana Rita Grosso, (PI)

Selected Publications

Prudêncio P, Rebelo K, Grosso AR, Martinho RG, Carmo-Fonseca M.. 2019. Analysis of Mammalian Native Elongating Transcript sequencing (mNET-seq) high-throughput data. METHODS, DOI: 10.1016/j.ymeth.2019.09.003
Mafalda Ramos de Matos; Ioana Posa; Filipa Sofia Carvalho; Vanessa Alexandra Morais; Ana Rita Grosso; Sérgio Fernandes de Almeida. 2019. A Systematic Pan-Cancer Analysis of Genetic Heterogeneity Reveals Associations with Epigenetic Modifiers. Cancers, DOI: 10.3390/cancers11030391
Alexandra CVítor; Sreerama CSridhara; João CSabino; Ana IAfonso; Ana RGrosso; Robert MMartin; Sérgio Fde Almeida. 2019. Single-molecule imaging of transcription at damaged chromatin. Science Advances, 5(1), DOI: 10.1126/sciadv.aau1249
Siwek, Wojciech; Gómez-Rodríguez, Mariluz; Sobral, Daniel; Corrêa, Ivan R; Jansen, Lars ET. 2018. time-ChIP: A Method to Determine Long-Term Locus-Specific Nucleosome Inheritance. Methods in molecular biology (Clifton, N.J.), DOI: 10.1007/978-1-4939-8663-7_7