Fran Supek

Prof. Fran Supek

Institució Catalana de Recerca i Estudis Avançats (ICREA), Lluís Companys 28, 08030 Barcelona, Spain
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Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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18 July 2011 in PLOS ONE
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Journal Article
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FSFran Supek
Fran Supek
MBMatko Bošnjak
Matko Bošnjak
NŠNives Škunca
Nives Škunca
TSTomislav Smuc
Tomislav Smuc
Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.

27 January 2013 in Nature Methods
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Journal Article
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PRPredrag Radivojac
Predrag Radivojac
WCWyatt T Clark
Wyatt T Clark
TOTal Ronnen Oron
Tal Ronnen Oron
ASAlexandra M Schnoes
Alexandra M Schnoes
TWTobias Wittkop
Tobias Wittkop
IFIddo Friedberg
Iddo Friedberg
A report on the results of the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high. Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.

12 September 2016 in Nature Genetics
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RLRik G H Lindeboom
Rik G H Lindeboom
FSFran Supek
Fran Supek
BLBen Lehner
Ben Lehner
Ben Lehner and colleagues analyze data from matched exomes and transcriptomes from tumors across 27 cancer types to elucidate rules linking premature termination codon location to nonsense-mediated mRNA decay (NMD). They propose a model that explains variability in NMD efficiency and find evidence of positive and negative selection on NMD-initiating mutations in tumors. Premature termination codons (PTCs) cause a large proportion of inherited human genetic diseases. PTC-containing transcripts can be degraded by an mRNA surveillance pathway termed nonsense-mediated mRNA decay (NMD). However, the efficiency of NMD varies; it is inefficient when a PTC is located downstream of the last exon junction complex (EJC). We used matched exome and transcriptome data from 9,769 human tumors to systematically elucidate the rules of NMD targeting in human cells. An integrated model incorporating multiple rules beyond the canonical EJC model explains approximately three-fourths of the non-random variance in NMD efficiency across thousands of PTCs. We also show that dosage compensation may sometimes mask the effects of NMD. Applying the NMD model identifies signatures of both positive and negative selection on NMD-triggering mutations in human tumors and provides a classification for tumor-suppressor genes.

1 March 2014 in Cell
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Journal Article
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FSFran Supek
Fran Supek
BMBelén Miñana
Belén Miñana
JVJuan Valcárcel
Juan Valcárcel
TGToni Gabaldon
Toni Gabaldon
BLBen Lehner
Ben Lehner

5 February 2020 in Nature Genetics
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BRBernardo Rodriguez-Martin
Bernardo Rodriguez-Martin
EAEva G. Alvarez
Eva G. Alvarez
ABAdrian Baez-Ortega
Adrian Baez-Ortega
JZJorge Zamora
Jorge Zamora
FSFran Supek
Fran Supek
JTJose M. C. Tubio
Jose M. C. Tubio
About half of all cancers have somatic integrations of retrotransposons. Here, to characterize their role in oncogenesis, we analyzed the patterns and mechanisms of somatic retrotransposition in 2,954 cancer genomes from 38 histological cancer subtypes within the framework of the Pan-Cancer Analysis of Whole Genomes (PCAWG) project. We identified 19,166 somatically acquired retrotransposition events, which affected 35% of samples and spanned a range of event types. Long interspersed nuclear element (LINE-1; L1 hereafter) insertions emerged as the first most frequent type of somatic structural variation in esophageal adenocarcinoma, and the second most frequent in head-and-neck and colorectal cancers. Aberrant L1 integrations can delete megabase-scale regions of a chromosome, which sometimes leads to the removal of tumor-suppressor genes, and can induce complex translocations and large-scale duplications. Somatic retrotranspositions can also initiate breakage–fusion–bridge cycles, leading to high-level amplification of oncogenes. These observations illuminate a relevant role of 22 L1 retrotransposition in remodeling the cancer genome, with potential implications for the development of human tumors.

23 February 2015 in Nature
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Journal Article
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FSFran Supek
Fran Supek
BLBen Lehner
Ben Lehner
An analysis of how regional mutation rates vary across 652 tumours identifies variable DNA mismatch repair as the basis of the characteristic regional variation in mutation rates seen across the human genome; the results show that differential DNA repair, rather than differential mutation supply, is likely to be the primary cause of this variation. Somatic mutation rates vary across the human genome in different cancers. Using comparative genomic analysis of 652 tumours, Fran Supek and Ben Lehner identify variable DNA mismatch repair (MMR) as the basis of the characteristic regional variation in mutation rates across the human genome. While regional autosomal mutation rates are largely stable across cell types, with differences related to changes in replication timing and gene expression, tumours with inactivated MMR have reduced regional mutation density variation. It therefore appears that differential DNA repair and not differential mutation supply is the primary cause of the large-scale regional mutation rate variation in the human genome. Cancer genome sequencing has revealed considerable variation in somatic mutation rates across the human genome, with mutation rates elevated in heterochromatic late replicating regions and reduced in early replicating euchromatin1,2,3,4,5. Multiple mechanisms have been suggested to underlie this2,6,7,8,9,10, but the actual cause is unknown. Here we identify variable DNA mismatch repair (MMR) as the basis of this variation. Analysing ∼17 million single-nucleotide variants from the genomes of 652 tumours, we show that regional autosomal mutation rates at megabase resolution are largely stable across cancer types, with differences related to changes in replication timing and gene expression. However, mutations arising after the inactivation of MMR are no longer enriched in late replicating heterochromatin relative to early replicating euchromatin. Thus, differential DNA repair and not differential mutation supply is the primary cause of the large-scale regional mutation rate variation across the human genome.