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3. Exploring the brain epitranscriptome: perspectives from the NSAS summit

Author

Lee, Sung-Min, Koo, B.K., Carre, Clement, Fischer, A., He, C., Kumar, A., Storkebaum, Erik, Yoon, K., Song, H., Lee, Sung-Min, Koo, B.K., Carre, Clement, Fischer, A., He, C., Kumar, A., Storkebaum, Erik, Yoon, K., and Song, H.

Abstract

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Published
2023

4. Positioning Europe for the EPITRANSCRIPTOMICS challenge

Author

Jantsch, Michael F., primary, Quattrone, Alessandro, additional, O'Connell, Mary, additional, Helm, Mark, additional, Frye, Michaela, additional, Macias-Gonzales, Manuel, additional, Ohman, Marie, additional, Ameres, Stefan, additional, Willems, Luc, additional, Fuks, Francois, additional, Oulas, Anastasis, additional, Vanacova, Stepanka, additional, Nielsen, Henrik, additional, Bousquet-Antonelli, Cecile, additional, Motorin, Yuri, additional, Roignant, Jean-Yves, additional, Balatsos, Nikolaos, additional, Dinnyes, Andras, additional, Baranov, Pavel, additional, Kelly, Vincent, additional, Lamm, Ayelet, additional, Rechavi, Gideon, additional, Pelizzola, Mattia, additional, Liepins, Janis, additional, Holodnuka Kholodnyuk, Irina, additional, Zammit, Vanessa, additional, Ayers, Duncan, additional, Drablos, Finn, additional, Dahl, John Arne, additional, Bujnicki, Janusz, additional, Jeronimo, Carmen, additional, Almeida, Raquel, additional, Neagu, Monica, additional, Costache, Marieta, additional, Bankovic, Jasna, additional, Banovic, Bojana, additional, Kyselovic, Jan, additional, Valor, Luis Miguel, additional, Selbert, Stefan, additional, Pir, Pinar, additional, Demircan, Turan, additional, Cowling, Victoria, additional, Schäfer, Matthias, additional, Rossmanith, Walter, additional, Lafontaine, Denis, additional, David, Alexandre, additional, Carre, Clement, additional, Lyko, Frank, additional, Schaffrath, Raffael, additional, Schwartz, Schraga, additional, Verdel, Andre, additional, Klungland, Arne, additional, Purta, Elzbieta, additional, Timotijevic, Gordana, additional, Cardona, Fernando, additional, Davalos, Alberto, additional, Ballana, Ester, additional, O´Carroll, Donal, additional, Ule, Jernej, additional, and Fray, Rupert, additional

Published
2018
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5. Positioning Europe for the EPITRANSCRIPTOMICS challenge

Author

Jantsch, Michael F., Quattrone, Alessandro, O'Connell, Mary, Helm, Mark, Frye, Michaela, Macias-Gonzales, Manuel, Ohman, Marie, Ameres, Stefan, Willems, Luc, Fuks, Francois, Oulas, Anastasis, Vanacova, Stepanka, Nielsen, Henrik, Bousquet-Antonelli, Cecile, Motorin, Yuri, Roignant, Jean-Yves, Balatsos, Nikolaos, Dinnyes, Andras, Baranov, Pavel, Kelly, Vincent, Lamm, Ayelet, Rechavi, Gideon, Pelizzola, Mattia, Liepins, Janis, Kholodnyuk, Irina Holodnuka, Zammit, Vanessa, Ayers, Duncan, Drablos, Finn, Dahl, John Arne, Bujnicki, Janusz, Jeronimo, Carmen, Almeida, Raquel, Neagu, Monica, Costache, Marieta, Banković, Jasna, Banović Đeri, Bojana, Kyselovic, Jan, Valor, Luis Miguel, Selbert, Stefan, Pir, Pinar, Demircan, Turan, Cowling, Victoria, Schaefer, Matthias, Rossmanith, Walter, Lafontaine, Denis, David, Alexandre, Carre, Clement, Lyko, Frank, Schaffrath, Raffael, Schwartz, Schraga, Verdel, Andre, Klungland, Arne, Purta, Elzbieta, Timotijević, Gordana, Cardona, Fernando, Davalos, Alberto, Ballana, Ester, O'Carroll, Donal, Ule, Jernej, Fray, Rupert, Jantsch, Michael F., Quattrone, Alessandro, O'Connell, Mary, Helm, Mark, Frye, Michaela, Macias-Gonzales, Manuel, Ohman, Marie, Ameres, Stefan, Willems, Luc, Fuks, Francois, Oulas, Anastasis, Vanacova, Stepanka, Nielsen, Henrik, Bousquet-Antonelli, Cecile, Motorin, Yuri, Roignant, Jean-Yves, Balatsos, Nikolaos, Dinnyes, Andras, Baranov, Pavel, Kelly, Vincent, Lamm, Ayelet, Rechavi, Gideon, Pelizzola, Mattia, Liepins, Janis, Kholodnyuk, Irina Holodnuka, Zammit, Vanessa, Ayers, Duncan, Drablos, Finn, Dahl, John Arne, Bujnicki, Janusz, Jeronimo, Carmen, Almeida, Raquel, Neagu, Monica, Costache, Marieta, Banković, Jasna, Banović Đeri, Bojana, Kyselovic, Jan, Valor, Luis Miguel, Selbert, Stefan, Pir, Pinar, Demircan, Turan, Cowling, Victoria, Schaefer, Matthias, Rossmanith, Walter, Lafontaine, Denis, David, Alexandre, Carre, Clement, Lyko, Frank, Schaffrath, Raffael, Schwartz, Schraga, Verdel, Andre, Klungland, Arne, Purta, Elzbieta, Timotijević, Gordana, Cardona, Fernando, Davalos, Alberto, Ballana, Ester, O'Carroll, Donal, Ule, Jernej, and Fray, Rupert

Abstract

The genetic alphabet consists of the four letters: C, A, G, and T in DNA and C,A,G, and U in RNA. Triplets of these four letters jointly encode 20 different amino acids out of which proteins of all organisms are built. This system is universal and is found in all kingdoms of life. However, bases in DNA and RNA can be chemically modified. In DNA, around 10 different modifications are known, and those have been studied intensively over the past 20years. Scientific studies on DNA modifications and proteins that recognize them gave rise to the large field of epigenetic and epigenomic research. The outcome of this intense research field is the discovery that development, ageing, and stem-cell dependent regeneration but also several diseases including cancer are largely controlled by the epigenetic state of cells. Consequently, this research has already led to the first FDA approved drugs that exploit the gained knowledge to combat disease. In recent years, the similar to 150 modifications found in RNA have come to the focus of intense research. Here we provide a perspective on necessary and expected developments in the fast expanding area of RNA modifications, termed epitranscriptomics.

Published
2018

6. Positioning Europe for the EPITRANSCRIPTOMICS challenge

Author

Jantsch, Michael F, Quattrone, Alessandro, O'Connell, Mary, Helm, Mark, Frye, Michaela, Macias-Gonzales, Manuel, Ohman, Marie, Ameres, Stefan, Willems, Luc, Fuks, Francois, Oulas, Anastasis, Vanacova, Stepanka, Nielsen, Henrik, Bousquet-Antonelli, Cecile, Motorin, Yuri, Roignant, Jean-Yves, Balatsos, Nikolaos, Dinnyes, Andras, Baranov, Pavel, Kelly, Vincent, Lamm, Ayelet, Rechavi, Gideon, Pelizzola, Mattia, Liepins, Janis, Holodnuka Kholodnyuk, Irina, Zammit, Vanessa, Ayers, Duncan, Drablos, Finn, Dahl, John Arne, Bujnicki, Janusz, Jeronimo, Carmen, Almeida, Raquel, Neagu, Monica, Costache, Marieta, Bankovic, Jasna, Banovic, Bojana, Kyselovic, Jan, Valor, Luis Miguel, Selbert, Stefan, Pir, Pinar, Demircan, Turan, Cowling, Victoria, Schäfer, Matthias, Rossmanith, Walter, Lafontaine, Denis, David, Alexandre, Carre, Clement, Lyko, Frank, Schaffrath, Raffael, Schwartz, Schraga, Verdel, Andre, Klungland, Arne, Purta, Elzbieta, Timotijevic, Gordana, Cardona, Fernando, Davalos, Alberto, Ballana, Ester, O Carroll, Donal, Ule, Jernej, Fray, Rupert, Jantsch, Michael F, Quattrone, Alessandro, O'Connell, Mary, Helm, Mark, Frye, Michaela, Macias-Gonzales, Manuel, Ohman, Marie, Ameres, Stefan, Willems, Luc, Fuks, Francois, Oulas, Anastasis, Vanacova, Stepanka, Nielsen, Henrik, Bousquet-Antonelli, Cecile, Motorin, Yuri, Roignant, Jean-Yves, Balatsos, Nikolaos, Dinnyes, Andras, Baranov, Pavel, Kelly, Vincent, Lamm, Ayelet, Rechavi, Gideon, Pelizzola, Mattia, Liepins, Janis, Holodnuka Kholodnyuk, Irina, Zammit, Vanessa, Ayers, Duncan, Drablos, Finn, Dahl, John Arne, Bujnicki, Janusz, Jeronimo, Carmen, Almeida, Raquel, Neagu, Monica, Costache, Marieta, Bankovic, Jasna, Banovic, Bojana, Kyselovic, Jan, Valor, Luis Miguel, Selbert, Stefan, Pir, Pinar, Demircan, Turan, Cowling, Victoria, Schäfer, Matthias, Rossmanith, Walter, Lafontaine, Denis, David, Alexandre, Carre, Clement, Lyko, Frank, Schaffrath, Raffael, Schwartz, Schraga, Verdel, Andre, Klungland, Arne, Purta, Elzbieta, Timotijevic, Gordana, Cardona, Fernando, Davalos, Alberto, Ballana, Ester, O Carroll, Donal, Ule, Jernej, and Fray, Rupert

Abstract

The genetic alphabet consists of the four letters: C, A, G, and T in DNA and C,A,G, and U in RNA. Triplets of these four letters jointly encode 20 different amino acids out of which proteins of all organisms are built. This system is universal and is found in all kingdoms of life. However, bases in DNA and RNA can be chemically modified. In DNA, around 10 different modifications are known, and those have been studied intensively over the past 20 years. Scientific studies on DNA modifications and proteins that recognize them gave rise to the large field of epigenetic and epigenomic research. The outcome of this intense research field is the discovery that development, ageing, and stem-cell dependent regeneration but also several diseases including cancer are largely controlled by the epigenetic state of cells. Consequently, this research has already led to the first FDA approved drugs that exploit the gained knowledge to combat disease. In recent years, the ~150 modifications found in RNA have come to the focus of intense research. Here we provide a perspective on necessary and expected developments in the fast expanding area of RNA modifications, termed epitranscriptomics.

Published
2018

7. Positioning Europe for the EPITRANSCRIPTOMICS challenge.

Author

Jantsch, Michael MF, Quattrone, Alessandro, O'Connell, Mary, Helm, Mark, Frye, Michaela, Macias-Gonzales, Manuel, Ohman, Marie, Ameres, Stefan, Willems, Lucas, Fuks, François, Oulas, Anastasis, Vanacova, Stepanka, Nielsen, Henrik, Bousquet-Antonelli, C, Motorin, Yuri, Roignant, Jean-Yves, Balatsos, Nikolaos, Dinnyes, Andras, Baranov, Pavel, Kelly, Vincent, Lamm, Ayelet, Rechavi, Gideon, Pelizzola, Mattia, Liepins, Janis, Holodnuka Kholodnyuk, Irina, Zammit, Vanessa, Ayers, Duncan, Drablos, Finn, Dahl, John Arne, Bujnicki, Janusz Marek, Jeronimo, Carmen, Almeida, Raquel, Neagu, Monica, Costache, Marieta, Bankovic, Jasna, Banovic, Bojana, Kyselovic, Jan, Valor, Luis Miguel, Selbert, Stefan, Pir, Pinar, Demircan, Turan, Cowling, Victoria, Schäfer, Matthias, Rossmanith, Walter, Lafontaine, Denis, David, Alexandre, Carre, Clement, Lyko, Frank, Schaffrath, Raffael, Schwartz, Schraga, Verdel, Andre, Klungland, Arne, Purta, Elzbieta, Timotijevic, Gordana, Cardona, F., Davalos, Alberto, Ballana, Ester, O Carroll, Donal, Ule, Jernej, Fray, Rupert, Jantsch, Michael MF, Quattrone, Alessandro, O'Connell, Mary, Helm, Mark, Frye, Michaela, Macias-Gonzales, Manuel, Ohman, Marie, Ameres, Stefan, Willems, Lucas, Fuks, François, Oulas, Anastasis, Vanacova, Stepanka, Nielsen, Henrik, Bousquet-Antonelli, C, Motorin, Yuri, Roignant, Jean-Yves, Balatsos, Nikolaos, Dinnyes, Andras, Baranov, Pavel, Kelly, Vincent, Lamm, Ayelet, Rechavi, Gideon, Pelizzola, Mattia, Liepins, Janis, Holodnuka Kholodnyuk, Irina, Zammit, Vanessa, Ayers, Duncan, Drablos, Finn, Dahl, John Arne, Bujnicki, Janusz Marek, Jeronimo, Carmen, Almeida, Raquel, Neagu, Monica, Costache, Marieta, Bankovic, Jasna, Banovic, Bojana, Kyselovic, Jan, Valor, Luis Miguel, Selbert, Stefan, Pir, Pinar, Demircan, Turan, Cowling, Victoria, Schäfer, Matthias, Rossmanith, Walter, Lafontaine, Denis, David, Alexandre, Carre, Clement, Lyko, Frank, Schaffrath, Raffael, Schwartz, Schraga, Verdel, Andre, Klungland, Arne, Purta, Elzbieta, Timotijevic, Gordana, Cardona, F., Davalos, Alberto, Ballana, Ester, O Carroll, Donal, Ule, Jernej, and Fray, Rupert

Abstract

The genetic alphabet consists of the four letters: C, A, G, and T in DNA and C,A,G, and U in RNA. Triplets of these four letters jointly encode 20 different amino acids out of which proteins of all organisms are built. This system is universal and is found in all kingdoms of life. However, bases in DNA and RNA can be chemically modified. In DNA, around 10 different modifications are known, and those have been studied intensively over the past 20 years. Scientific studies on DNA modifications and proteins that recognize them gave rise to the large field of epigenetic and epigenomic research. The outcome of this intense research field is the discovery that development, ageing, and stem-cell dependent regeneration but also several diseases including cancer are largely controlled by the epigenetic state of cells. Consequently, this research has already led to the first FDA approved drugs that exploit the gained knowledge to combat disease. In recent years, the ~150 modifications found in RNA have come to the focus of intense research. Here we provide a perspective on necessary and expected developments in the fast expanding area of RNA modifications, termed epitranscriptomics., SCOPUS: no.j, info:eu-repo/semantics/published

Published
2018

8. Reverse engineering highlights potential principles of large gene regulatory network design and learning

Author

Carre, Clement, Mas, André, Krouk, Gabriel, Biochimie et Physiologie Moléculaire des Plantes (BPMP), Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Institut Montpelliérain Alexander Grothendieck (IMAG), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Equipe Hormones, Nutriments et Développement (HoNuDe) (HONUDE), Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Escherichia coli K14, Vegetal Biology, QH301-705.5, régulation des gènes transcriptionnels, réseaux régulateurs de gènes, Article, ChIP-seq, moteur de simulation FRANK, données transcriptomiques, technique d'évaluation expérimentales, DAP-seq, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, ComputingMethodologies_GENERAL, Biology (General), Biologie végétale
Abstract

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 104 genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data (Escherichia coli K14 network reconstruction using network and transcriptomic data), we show that the formalism used to build FRANK can to some extent be a reasonable model for gene regulatory networks in real cells., Gene Regulatory Networks: design and learning principles This work by Carré et al addresses central questions in biology, which are: how very large gene regulatory networks (GRNs) are organized, generate stable gene expression, and can be learnt using machine learning algorithms? In this work authors developed an algorithm able to simulate large GRNs. From these networks they simulate stable or oscillating gene expression and highlights some mathematical rules controlling such a collective (several thousands of genes) behavior. They discuss consequent hypothesis concerning the organization of GRNs in real cells. Using this simulation tool, authors also demonstrate that it’s likely possible to computationally learn GRNs from transcriptomic data and prior knowledge on the network (actual known connections issued from Yeast One Hybrid or ChIP Seq for instance). They particularly highlight the crucial importance of the prior knowledge structure in their capacity to learn large GRNs.

Published
2017
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