L'unité MIG et l'unité MIAJ ont fusionné au 1er janvier 2015. Elles constituent dorénavant la nouvelle unité MaIAGE dont le site internet est accessible via l'URL suivante : http://maiage.jouy.inra.fr.

Séminaires 2009

Les séminaires ont en général lieu dans la bibliothèque du batiment MIG (233).
Contact :François Rodolphe (poste 2889)

2009

2eme semestre 2009

vendredi 2 octobre
11h30
Hugues Richard
Computational Molecular Biology Group, Max Planck Institut für molekülare Genetik. Berlin
Renseignements auprès de :
Pierre.Nicolas@jouy.inra.fr
Genome Wide Analysis of the transcriptome by second generation sequencing.
The functional complexity of the human transcriptome is not yet fully elucidated. We report a high-throughput sequence of the human transcriptome from a human embryonic kidney and a B cell line. We used shotgun sequencing of transcripts to generate randomly distributed reads. Of these, 50% mapped to unique genomic locations, of which 80% corresponded to known exons. We found that 66% of the polyadenylated transcriptome mapped to known genes and 34% to non annotated genomic regions. On the basis of known transcripts, RNA-Seq can detect 25% more genes than can microarrays. A global survey of messenger RNA splicing events identified 94,241 splice junctions (4096 of which were previously unidentified) and showed that exon skipping is the most prevalent form of alternative splicing. Furthermore, we propose a set of statistical procedures to infer alternative splicing events and quantify isoform proportions from RNA-Seq experiments. The approach, that combines hypothesis testing and EM estimation, was evaluated by RT-PCR-based experimental validations and by comparison with exon array data.

1er semestre 2009

mercredi 18 mars
14h30
Eric Rivals
LIRMM, Montpellier
Renseignements auprès de :
Sophie.Schbath@jouy.inra.fr
Estimation of sequence errors and prediction capacity in transcriptomic and DNA-protein interaction assays.
Next-generation sequencing technologies, able to yield millions of sequences in a single run, allow to interrogate the transcriptome or to assay protein-DNA interactions (by Chromatin ImmunoPrecipitation by sequencing or ChIP-seq) at a genome-wide scale. These assays yield short sequences (<40 bp), called tags, that need to be mapped to the genome sequence. To each tag is associated the number of times the same sequence has been experimentally detected : its occurrence number. For transcriptomic assays, for instance, a tag with a high occurrence number likely is the biologically valid signature of an abundant transcript, while a tag with a low occurrence number may either result from a sequencing error or identify a rare RNA. The mapping is a compulsory step to first predict, and then annotate regions of interest on the genome. Usually, only genomic locations that are unambiguously mapped by a tag are further analysed. Those high-throughput assays are intended to predict a maximum number of genomic locations of interest. Obviously, this induces a balance between the number of mapped tags and the number of tags that map a unique genomic location, and this balance is controlled by the tag length. The sequencing technique generally dictates the tag length. Nevertheless, once a certain length is sequenced (e.g., 36 bp with a Solexa/Illumina 1G machine) it is still possible to map only sub-parts (a prefix, a suffix, a substring) of the tags to the genome, thereby artificially reducing the tag length and modifying the balance. Presently, we lack a statistical method to evaluate the influence of the tag length on the capacity of prediction for different assays and sequencing techniques, as well as the importance of sequence errors. Our contribution is threefold. Based on word statistics, we design a program that computes the theoretical probability of mapping a genomic location by chance for a given tag length. Using an efficient algorithm to map short tags on complete genome sequence, we investigate how the prediction capacity varies with tag length. Finally, we propose a method to estimate the probability of a tag to be altered by a sequencing error. We apply it to derive a probability of having an erroneous nucleotide at a given position in the tag for the Sanger and Solexa sequencing techniques, and for both transcriptomic and ChIP-seq experiments. This enables a technical assessment of such assays and the indirect measurement of the impact of some biological phenomena.
Vendredi 16 janvier
14h
Vincent Plagnol
Cambridge Diabetes and Inflammation Laboratory
Renseignements auprès de :
Pierre.Nicolas@jouy.inra.fr
L'architecture génetique du diabète de type 1 et ses liens avec les maladies coeliaque et de Crohn.
Les récentes études de cas-temoins ont revolutionné notre compréhension des facteurs génétiques de risque vis-à-vis des maladies auto-immunes, en particulier le diabète de type 1 (T1D). Un résultat surprenant de ces études est le grand nombre de locus qui sont partagés par de multiples maladies auto-immunes, comme la maladie de Crohn, la maladie coeliaque, T1D ou la sclérose en plaques. Ces facteurs communs montrent que des mécanismes similaires sont partagés par ces maladies, qui sont en fait tres liées. L'orateur présentera les récentes avancées de son laboratoire dans la compréhension des facteurs génétiques du T1D, et de ses liens avec les maladies coeliaques et de Crohn. Il montrera ensuite comment il prévoit d'utiliser ces découvertes génétiques pour mieux comprendre les mécanismes moléculaires qui causent ces maladies.