Cookies Policy
We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out More
Close
  • Menu
Interest
Topics
Details

Details

  • Name

    Nuno Fonseca
  • Cluster

    Computer Science
  • Role

    External Research Collaborator
  • Since

    01st June 2009
Publications

2019

ArrayExpress update – from bulk to single-cell expression data

Authors
Athar, A; Fullgrabe, A; George, N; Iqbal, H; Huerta, L; Ali, A; Snow, C; Fonseca, NA; Petryszak, R; Papatheodorou, I; Sarkans, U; Brazma, A;

Publication
Nucleic Acids Research

Abstract

2019

A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters

Authors
Demircioglu, D; Cukuroglu, E; Kindermans, M; Nandi, T; Calabrese, C; Fonseca, NA; Kahles, A; Kjong Van Lehmann,; Stegle, O; Brazma, A; Brooks, AN; Ratsch, G; Tan, P; Goke, J;

Publication
Cell

Abstract
Alternative promoters are frequently used to regulate tissue- and cancer-specific transcription, and variation in promoter usage is associated with cancer patient survival. © 2019 Elsevier Inc.Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. However, while a global change in transcription is recognized as a defining feature of cancer, the contribution of alternative promoters still remains largely unexplored. Here, we infer active promoters using RNA-seq data from 18,468 cancer and normal samples, demonstrating that alternative promoters are a major contributor to context-specific regulation of transcription. We find that promoters are deregulated across tissues, cancer types, and patients, affecting known cancer genes and novel candidates. For genes with independently regulated promoters, we demonstrate that promoter activity provides a more accurate predictor of patient survival than gene expression. Our study suggests that a dynamic landscape of active promoters shapes the cancer transcriptome, opening new diagnostic avenues and opportunities to further explore the interplay of regulatory mechanisms with transcriptional aberrations in cancer. © 2019 Elsevier Inc.

2018

Expression Atlas: gene and protein expression across multiple studies and organisms

Authors
Papatheodorou, I; Fonseca, NA; Keays, M; Tang, YA; Barrera, E; Bazant, W; Burke, M; Füllgrabe, A; Pomer Fuentes, AM; George, N; Huerta, L; Koskinen, S; Mohammed, S; Geniza, MJ; Preece, J; Jaiswal, P; Jarnuczak, A; Huber, W; Stegle, O; Vizcaíno, JA; Brazma, A; Petryszak, R;

Publication
Nucleic Acids Research

Abstract

2018

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Authors
Tello Ruiz, MK; Naithani, S; Stein, JC; Gupta, P; Campbell, M; Olson, A; Wei, S; Preece, J; Geniza, MJ; Jiao, Y; Lee, YK; Wang, B; Mulvaney, J; Chougule, K; Elser, J; Bader, NA; Kumari, S; Thomason, J; Kumar, V; Bolser, DM; Naamati, G; Tapanari, E; Fonseca, NA; Huerta, L; Iqbal, H; Keays, M; Pomer Fuentes, AM; Tang, YA; Fabregat, A; D'Eustachio, P; Weiser, J; Stein, LD; Petryszak, R; Papatheodorou, I; Kersey, PJ; Lockhart, P; Taylor, C; Jaiswal, P; Ware, D;

Publication
Nucleic Acids Research

Abstract

2018

Inferences on specificity recognition at the Malusxdomestica gametophytic self-incompatibility system

Authors
Pratas, MI; Aguiar, B; Vieira, J; Nunes, V; Teixeira, V; Fonseca, NA; Iezzoni, A; van Nocker, S; Vieira, CP;

Publication
SCIENTIFIC REPORTS

Abstract
In Malus x domestica (Rosaceae) the product of each SFBB gene (the pollen component of the gametophytic self-incompatibility (GSI) system) of a S-haplotype (the combination of pistil and pollen genes that are linked) interacts with a sub-set of non-self S-RNases (the pistil component), but not with the self S-RNase. To understand how the Malus GSI system works, we identified 24 SFBB genes expressed in anthers, and determined their gene sequence in nine M. domestica cultivars. Expression of these SFBBs was not detected in the petal, sepal, filament, receptacle, style, stigma, ovary or young leaf. For all SFBBs (except SFBB15), identical sequences were obtained only in cultivars having the same S-RNase. Linkage with a particular S-RNase was further established using the progeny of three crosses. Such data is needed to understand how other genes not involved in GSI are affected by the S-locus region. To classify SFBBs specificity, the amino acids under positive selection obtained when performing intra-haplotypic analyses were used. Using this information and the previously identified S-RNase positively selected amino acid sites, inferences are made on the S-RNase amino acid properties (hydrophobicity, aromatic, aliphatic, polarity, and size), at these positions, that are critical features for GSI specificity determination.