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Équipe Gianni LITI

Presentation

Equipe de Recherche Fondamentale  « Population genomics and complex traits  »


Dr Gianni LITI, CR1 CNRS, Chef d'Equipe




photo 2014

De gauche à droite  : Johan Hallin, Benjamin Barre, Gianni Liti, Agnès Llored, Matteo De Chiara, Jiaxing Yue, Jing Li.

 

Résumé


Most human traits, including cancer susceptibility and ageing, are regulated by multiple interacting quantitative trait loci (QTLs). Dissecting the genetic mechanisms underlying this phenotypic variation is a major challenge. In order to advance our understanding of complex traits there is a need for a suitable genetic system that can be used in high-throughput studies. In our lab, we use the budding yeast, S. cerevisiae, to dissect the genetic architecture of multiple traits. The objectives are relevant for human health in two ways: the first consists of modelling complex traits in a simple genetic system; the second aims to dissect traits directly relevant to the complex biology of cancer and ageing. In all aspects of our research, we exploit natural variation in the budding yeast as a tool for understanding how a phenotype is genetically regulated. Given that many pathways (e.g. longevity) are conserved from yeast to humans, there is an opportunity to test previously uncharacterised genes in other model systems. Once the architecture of complex traits is fully dissected, the next step is to extrapolate this knowledge to make predictions (based on population genomics data) of the standing variation in natural populations. Finally, the long-term challenge is to understand what evolutionary forces maintain the variability in natural populations.


Projet de Recherche

Projet de Recherche


Our past and present areas of research are :


1. Telomeres and genomic instability: telomere maintenance in the absence of telomerase in S. cerevisiae. Telomerase negative yeast has been an excellent model for understanding the underlying genetic mechanisms leading to ALT (alternative lengthening of telomeres) tumours and associated genomic instability. We have found dramatic differences in genome stability rates between haploid and diploid cells, in the absence of telomerase. We have also shown a paradoxical role for a gene, NEJ1, which promotes DNA repair in wild type cells while protecting the telomere from end fusions in telomerase negative cells.


2. Exploiting natural variation to map quantitative trait loci (QTLs) of various telomere properties including length, silencing, ageing, and senescence. We have found dramatic differences in telomere length and telomeric transcriptional silencing in natural population. We are characterising this variation with the aim to identify novel genes that affect telomeric properties. One of the QTL that contribute to telomere length variation is the RNA template of telomerase (hortolog of hTERT) and allelic variants of this gene are associated with telomere length variation in human populations.


3. Evolution of the RAS signalling pathway. This pathway is highly conserved in all eukaryotes and is a key regulator of cell growth and malignant transformation. We found that widespread sequence variation in this pathway regulate internal levels of cAMP and contribute to quantitative differences in ageing (chronological life span), virulence (ability to grow at high temperature) and mitochondrial genome stability. Part of the variation in the RAS signalling pathway is due to sequence polymorphisms in the IRA1 and IRA2. The IRA genes are of specific interest as they are highly conserved orthologs of the human disease gene NF1, which causes neurofibromatosis type 1, and as mutations in patients with neurofibromatosis also have similar detrimental effects on the yeast Ira1p activity.


4. Genome evolution. Our studies on genome evolution lay the foundation for understanding the population structure of Saccharomyces yeasts and highlighted how classical phylogeny is inadequate to present the true relationship between strains and species. We are also interested in the relationship between sequence divergence and meiotic sterility.


5. Population genomics. I have been part of a joint effort, the Saccharomyces Genome Resequencing Project (SGRP), involving Richard Durbin’s group at The Sanger Institute and Edward Louis’ group at Universtiy of Nottingham to sequence and release genome sequence data of 72 strains of S. cerevisiae and its closest known species S. paradoxus. This study led to a landmark paper published in March 2009 that initiate the field of population genomics and revealed the impact of human activity on the population structure of the baker’s yeast.


Equipe de Recherche

Equipe de Recherche



LITI Gianni, CR1 CNRS, Team Leader
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BARRE Benjamin, PhD Student
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D'ANGIOLO Mélania, Master ERASMUS

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DE CHIARA Matteo, CDD CR CNRS

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HALLIN Johan, PhD Student
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IRIZAR ONA Agurtzane, CDD IE CNRS

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LI Jing, CDD CR CNRS Research Scientist

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LLORED Agnès, Univ. Technician
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POULLET Marine, M1 Student
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YUE Jia-Xing, CDD CR CNRS

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(Jan 2017)





Presse/Medias

Avril 2017 :


Gianni LITI, chef d'Equipe à l'IRCAN, vient de publier un article sur les

"Contrasting evolutionary genome dynamics between domesticated and wild yeasts" dans la prestigieuse revue "Nature Genetics".

https://www.ncbi.nlm.nih.gov/pubmed/28416820


Résumé français :


Cela fait plus de 150 ans que le moine Autrichien Gregor Mendel réalisa ses célèbres expériences sur la couleur et la texture des petits pois. Depuis lors, les scientifiques s'efforcent d'expliquer comment l'information génétique codée dans notre ADN se traduit en traits physiques observables, appelés phénotypes. Au cours de ces dernières années, le développement rapide des techniques de séquençage nous a permis de décoder plus facilement la séquence de notre ADN. Pour ce faire, on commence par découper l'ADN en millions de petits fragments puis on séquence ces petits fragments à très large échelle. Cependant, réorganiser ces petits moreaux de séquences entre eux n'est pas chose facile, un peu comme assembler un immense puzzle avec des pièces manquantes et plusieurs pièces qui peuvent aller au même endroit. De plus, il y a de nombreuses régions dans nos chromosomes qui sont réarrangées et ces variations structurelles sont difficiles, voire impossibles dans certains cas,  à assembler avec des séquences de petite taille. En conséquence, une grande proportion de ces régions reste indéterminée alors que de nombreux indices suggèrent qu'elles joueraient un rôle très important dans l'adaptation à l'environnement et la susceptibilité aux maladies.


L'avènement récent des technologies de séquençage de longs fragments d'ADN s'est révélé être très puissant pour assembler des génomes complets et pour résoudre correctement les régions complexes et réarrangées. Cependant, ceci avait été réalisé jusqu'à présent uniquement à l'échelle de génome de référence unique. Un consortium international dirigé par Jia-Xing Yue et Gianni Liti a maintenant étendu cette approche à un niveau supérieur. Ils ont séquencé les génomes de 12 souches représentatives de la levure de boulangerie (Saccharomyces cerevisiae), partiellement domestiquées par l'homme, et d'une levure apparentée mais qui est restée à l'état sauvage (Saccharomyces paradoxus). Ils ont reconstruit des génomes entièrement assemblés, d'un bout à l'autre des chromosomes, produisant ainsi le premier jeu de données génomiques de ce type à l'échelle d'une population. En comparant de manière systématique ces séquences génomiques, à la fois entre souches de la même espèce mais aussi entre souches appartenant aux deux espèces différentes, ils ont pu décrire précisément la dynamique structurelle des génomes dans leur contexte évolutif. Ceci leur a permi de mettre en évidence des contrastes frappant entre ces 2 espèces qui, pour la plupart, peuvent être expliqué par l'association étroite entre la levure de boulangerie et les activités humaines. De plus les régions localisées proches des extrémités des chromosomes, appelées "subtélomères", évoluent très rapidement et accumulent de nombreux réarrangements structuraux.


Cette étude fournit la première définition précise de ces régions chromosomiques complexes et illustre leur plasticité évolutive avec un niveau de résolution inédit. Enfin, ils montrent comment la résolution des réarrangements dans ces régions complexes peut nous éclairer pour comprendre les bases génétiques à l'origine des phénotypes complexes.


L'ensemble des données générées au cours de ce travail est mis à la disposition du public et de la communauté scientifique. Les assemblages complets des chromosomes ainsi que leurs annotations serviront de génomes de référence au niveau populationnel. Cette étude pose un nouveau jalon dans le champ de la génomique eucaryote et ouvre la voie à une meilleure compréhension de la relation génotype-phénotype. Les cellules cancéreuses sont également connues pour être particulièrement sujettes aux réarrangements chromosomiques et à l'instabilité génomique. La prochaine étape du consortium sera d'appliquer la même technologie de séquençage de longues molécules d'ADN aux cellules tumorales afin d'identifier les modifications génétiques à l'origine de l'instabilité génomique, ce qui pourrait permettre de trouver de nouvelles cibles pour le développement de thérapies anti-cancéreuses.




Janvier 2014 :


Publications

Publications


http://www.ncbi.nlm.nih.gov/pubmed/?term=liti+g



Laureau R, Loeillet S, Salinas F, Bergström A, Legoix-Né P, Liti G, Nicolas A.

Extensive Recombination of a Yeast Diploid Hybrid through Meiotic Reversion.

PLoS Genet., 2016, Feb 1;12(2):e1005781.


Liti G.

Yeast 2.0: a new chapter.

Yeast, 2016, Jan;33(1):3-4.



Ibstedt S, Stenberg S, Bagés S, Gjuvsland AB, Salinas F, Kourtchenko O, Samy JK, Blomberg A,

Omholt SW, Liti G, Beltran G, Warringer J.

Concerted evolution of life stage performances signals recent selection on yeast nitrogen use.

Mol Biol Evol., 2015, Jan;32(1):153-61.


Long A, Liti G, Luptak A, Tenaillon O.

Elucidating the molecular architecture of adaptation via evolve and resequence experiments

Nat Rev Genet., 2015, Oct;16(10):567-82.


Liti G.

The fascinating and secret wild life of the budding yeast S. cerevisiae.

Elife, 2015, Mar 25;4. Review.


López-Martínez G, Margalef-Català M, Salinas F, Liti G, Cordero-Otero R.

ATG18 and FAB1 are involved in dehydration stress tolerance in Saccharomyces cerevisiae.

PLoS One., 2015, Mar 24;10(3):e0119606.


Gibson B, Liti G.

Saccharomyces pastorianus: genomic insights inspiring innovation for industry.

Yeast, 2015, Jan;32(1):17-27.


Romagnoli G, Knijnenburg TA, Liti G, Louis EJ, Pronk JT, Daran JM.

Deletion of the Saccharomyces cerevisiae ARO8 gene, encoding an aromatic amino acid transaminase,

enhances phenylethanol production from glucose.

Yeast, 2015, Jan;32(1):29-45.



Marie-Nelly H, Marbouty M, Cournac A, Flot JF, Liti G, Parodi DP, Syan S, Guillén N,

Margeot A, Zimmer C, Koszul R.

High-quality genome (re)assembly using chromosomal contact data.

Nat Commun., 2014, Dec ;17(5):5695.


Burke MK, Liti G, Long AD.

Standing Genetic Variation Drives Repeatable Experimental Evolution in

Outcrossing Populations of Saccharomyces cerevisiae.

Mol. Biol. Evol., 2014, Dec ; 31(12):3228-39.


Marie-Nelly H, Marbouty M, Cournac A, Liti G, Fischer G, Zimmer C, Koszul R.

Filling annotation gaps in yeast genomes using genome-wide contact maps.

Bioinformatics, 2014, Aug 1;30(15):2105-13.


Wimalasena TT, Greetham D, Marvin ME, Liti G, Chandelia Y, Hart A, Louis EJ, Phister TG, Tucker GA, Smart KA.

Phenotypic characterisation of Saccharomyces spp.yeast for tolerance to stresses encountered during

fermentation of lignocellulosic residues to produce bioethanol.

Microb. Cell. Fact., 2014, Mar 27;13(1):47.


Jara M, Cubillos FA, García V, Salinas F, Aguilera O, Liti G, Martínez C.

Mapping genetic variants underlying differences in the central nitrogen metabolism in fermenter yeasts.

PLoS One, 2014, Jan 21;9(1):e86533.


Brown WR, Thomas G, Lee NC, Blythe M, Liti G, Warringer J, Loose MW.

Kinetochore assembly and heterochromatin formation occur autonomously in Schizosaccharomyces pombe.

Proc. Natl. Acad. Sci. USA, 2014, Feb 4;111(5):1903-8.


Bergström A, Simpson JT, Salinas F, Barré B, Parts L, Zia A, Nguyen Ba AN, Moses AM, Louis EJ,

Mustonen V, Warringer J, Durbin R, Liti G.

A high-definition view of functional genetic variation from natural yeast genomes.

Mol. Biol. Evol., 2014, Apr;31(4):872-88.


Louvel H, Gillet-Markowska A, Liti G, Fischer G.

A set of genetically diverged Saccharomyces cerevisiae strains with markerless deletions of

multiple auxotrophic genes.

Yeast, 2014, Mar;31(3):91-101.



Cubillos FA, Parts L, Salinas F, Bergström A, Scovacricchi E, Zia A, Illingworth CJ, Mustonen V,

Ibstedt S, Warringer J, Louis EJ, Durbin R, Liti G.

High resolution mapping of complex traits with a four-parent advanced intercross yeast population.

Genetics, 2013, 195(3):1141-55.


Illingworth CJ, Parts L, Bergström A, Liti G, Mustonen V.

Inferring genome-wide recombination landscapes from advanced intercross lines: application to yeast crosses.

PLoS One, 2013, 8(5) :E62266.


Zörgö E, Chwialkowska K, Gjuvsland A, Garre E, Sunnerhagen P, Liti G, Blomberg A, Omholt SW, Warringer J.

Ancient evolutionary trade-offs between yeast ploidy states.

PLoS Genetics, 2013, 9(3) :E1003388.


Dunn B, Paulish T, Stanbery A, Piotrowski J, Koniges G, Kroll E, Louis EJ, Liti G,

Sherlock G, Rosenzweig F.

Recurrent rearrangement during adaptive evolution in an interspecific yeast hybrid suggests a

model for rapid introgression.

PLoS Genetics, 2013, 9(3) :E1003366.


Liti G, Nguyen Ba AN, Blythe M, Müller CA, Bergström A, Cubillos FA, Dafhnis-Calas F, Khoshraftar S,

Malla S, Mehta N, Siow CC, Warringer J, Moses AM, Louis EJ, Nieduszynski CA.

High quality de novo sequencing and assembly of the Saccharomyces arboricolus genome.

BMC Genomics, 2013, 14(1):69.


Abbas C, Kurtzman C, Liti G.

ICY 2012 highlights.

Yeast, 2013, 30(8):293-4.



Salinas F, Cubillos FA, Soto D, Garcia V, Bergström A, Warringer J, Ganga MA, Louis EJ, Liti G, Martinez C.

The genetic basis of natural variation in oenological traits in Saccharomyces cerevisiae.

PLoS One, 2012, 7(11), e49640.


Armstrong J, Davis D, Liti G, Oliver S.

'New' yeasts for a new Yeast.

Yeast, 2012, 29(10), 407.


Liti G, Louis EJ.

Advances in quantitative trait analysis in yeast.

PLoS Genetics, 2012, 8(8), e1002912.


Wang Q-M, Liu W-Q, Liti G, Wang SA, Bai F-Y.

Surprisingly diverged populations of Saccharomyces cerevisiae in natural environments remote from human activity.

Molecular Ecology, 2012, 21(22), 5404-17.


McLaughlan MJ, Liti G, Sharp S, Maslowska A, Louis EJ.

Apparent ploidy effects on silencing are post-transcriptional at HML and telomeres in Saccharomyces cerevisiae.

PLoS One, 2012, 7(7), e39044.


Zörgö E, Gjuvsland A, Cubillos FA, Louis EJ, Liti G, Blomberg A, Omholt SW, Warringer J.

Life history shapes trait heredity by promoting accumulation of loss-of-function alleles in yeast.

Molecular Biology and Evolution, 2012, 29(7), 1781-9.


Illingworth CJ, Parts L, Schiffels S, Liti G, Mustonen V.

Quantifying selection acting on a complex trait using allele frequency time-series data. Molecular Biology and Evolution, 2012, 29(4), 1187-97.



Brown WRA, Liti G, Rosa C, James S, Roberts I, Robert V, Jolly N, Tang W, Baumann P, Green C, Schlegel K, Young J, Hirchaud F, Leek S, Thomas G, Blomberg A, Warringer J.

A Geographically diverse collection of Schizosaccharomyces pombe isolates shows limited phenotypic variation but extensive karyotypic diversity.

G3: Genes, Genomes, Genetics, 2011, 1(7), 615-26.


Liti G, Schacherer J.

The rise of yeast population genomics.

Comptes Rendus Biologies, 2011, 334 (8-9), 612-619.


Warringer J, Zörgö E, Cubillos FA, Zia A, Gjuvsland A, Simpson JT, Forsmark A, Durbin R, Omholt SW, Louis EJ, Liti G, Moses AM, Blomberg A.

Trait variation in yeast is defined by population history.

PLoS Genetics, 2011, 7(6), e1002111.


Parts L, Cubillos FA, Warringer J, Jain K, Salinas F, Bumpstead SJ, Molin M, Zia A, Simpson JT, Quail MA, Moses AM, Louis EJ, Durbin R, Liti G.

Revealing the genetic structure of a trait by sequencing a population under selection.

Genome Research, 2011, 21(7), 1131-8.


Nieduszynski CA, Liti G.

From sequence to function: insights from natural variation in budding yeasts.

Biochemical Biophysical Acta, 2011, 1810 (10), 959-66.


Cubillos FA, Billi E, Zörgö E, Parts L, Fargier P, Omholt S, Blomberg A, Warringer J,

Louis EJ, Liti G.

Assessing the Complex Architecture of polygenic traits in yeast.

Molecular Ecology, 2011, 20(7), 1401-13.



Cubillos FA, Louis EJ, Liti G.

Generation of a large set of genetically tractable haploid and diploid Saccharomyces strains.

FEMS Yeast Research, 2009, 9, 1217-1225.


Liti G, Haricharan S, Cubillos FA, Tierney AL, Sharp S, Bertuch AA, Parts L, Bailes E, Louis EJ.

Segregating YKU80 and TLC1 alleles underlying natural variation in telomere properties in wild yeast.

PLoS Genetics, 2009, 5 (9); e1000659.


Liti G, Carter DM, Moses AM, Warringer J, Parts L, James SA, Davey RP, Roberts IN, Burt A, Koufopanou V, Tsai IJ, Bergman CM, Bensasson D, O’Kelly MJT, van Oudenaarden A, Barton DBH, Bailes E, Nguyen Ba AN, Jones M, Quail MA, Goodhead I, Sims S, Smith F, Blomberg A, Durbin R and Louis EJ.

Population genomics of domestic and wild yeasts.

Nature, 2009, 19; 458(7236), 337-41.


Prix/Distinctions

Un chercheur de l'IRCAN récipiendaire d'un "Dupont Young Professor Award"


Gianni Liti, Chargé de Recherche CNRS et Chef d'équipe à l'IRCAN (CAL-CHU-CNRS-INSERM-UNS) fait parti des 9 récipiendaires d'un "Dupont Young Professor Award" en reconnaissance de la qualité et de l'innovation de sa recherche. L'équipe de recherche du Dr Liti s'articule autour de la génomique fonctionnelle. Il disposera d'une ligne budgétaire de 50 000 dollars pour optimiser sa recherche. Juin 2015. Plus d'informations

Financements

Financements


2013


1)  “Yeast complex trait genetics : beyond classical crosses” grant coordinator, co-applicants : Alain Nicolas (Institut Curie, Paris) and Sylvie Dequin (INRA, Montpellier) funded by ANR Programme Blanc, 3.5-years.


2) “The 1002 yeast genomes project : a framework for genome-wide association studies” co-applicant with Prof. Schacherer, funded by the France Génomique within the call Grands Projets de Séquençage.


2012


1)  Marie Curie Career Integration Grant “Modelling the complexity of ageing in a simple genetic system”, 4-years.


2011


1)  “Modelling the complexity of cancer in a simple genetic system”, funded by Association pour la Recherche sur le Cancer (ARC), 2-years.


2)  “Understanding the genetic mechanisms underlying quantitative traits” ATIP-AVENIR program funded by CNRS and INSERM, 3-years, 2 years extension possible.



Nov 2014