Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Colette Désert is active.

Publication


Featured researches published by Colette Désert.


BMC Genomics | 2008

Transcriptome profiling of the feeding-to-fasting transition in chicken liver

Colette Désert; M. J. Duclos; Pierre Blavy; Frédéric Lecerf; François Moreews; Christophe Klopp; Marc Aubry; Frédéric Hérault; Pascale Le Roy; Cécile Berri; Madeleine Douaire; Christian Diot; Sandrine Lagarrigue

BackgroundStarvation triggers a complex array of adaptative metabolic responses including energy-metabolic responses, a process which must imply tissue specific alterations in gene expression and in which the liver plays a central role. The present study aimed to describe the evolution of global gene expression profiles in liver of 4-week-old male chickens during a 48 h fasting period using a chicken 20 K oligoarray.ResultsA large number of genes were modulated by fasting (3532 genes with a pvalue corrected by Benjamini-Hochberg < 0.01); 2062 showed an amplitude of variation higher than +/- 40% among those, 1162 presented an human ortholog, allowing to collect functional information. Notably more genes were down-regulated than up-regulated, whatever the duration of fasting (16 h or 48 h). The number of genes differentially expressed after 48 h of fasting was 3.5-fold higher than after 16 h of fasting. Four clusters of co-expressed genes were identified by a hierarchical cluster analysis. Gene Ontology, KEGG and Ingenuity databases were then used to identify the metabolic processes associated to each cluster. After 16 h of fasting, genes involved in ketogenesis, gluconeogenesis and mitochondrial or peroxisomal fatty acid beta-oxidation, were up-regulated (cluster-1) whereas genes involved in fatty acid and cholesterol synthesis were down-regulated (cluster-2). For all genes tested, the microarray data was confirmed by quantitative RT-PCR. Most genes were altered by fasting as already reported in mammals. A notable exception was the HMG-CoA synthase 1 gene, which was up-regulated following 16 and 48 h of fasting while the other genes involved in cholesterol metabolism were down-regulated as reported in mammalian studies. We further focused on genes not represented on the microarray and candidates for the regulation of the target genes belonging to cluster-1 and -2 and involved in lipid metabolism. Data are provided concerning PPARa, SREBP1, SREBP2, NR1H3 transcription factors and two desaturases (FADS1, FADS2).ConclusionThis study evidences numerous genes altered by starvation in chickens and suggests a global repression of cellular activity in response to this stressor. The central role of lipid and acetyl-CoA metabolisms and its regulation at transcriptional level are confirmed in chicken liver in response to short-term fasting. Interesting expression modulations were observed for NR1H3, FADS1 and FADS2 genes. Further studies are needed to precise their role in the complex regulatory network controlling lipid metabolism.


Poultry Science | 2009

Liver X receptor α regulates fatty acid synthase expression in chicken

Olivier Demeure; C. Duby; Colette Désert; S. Assaf; Dominique Hazard; Hervé Guillou; Sandrine Lagarrigue

Liver X receptor alpha (LXRalpha), also referred to as nuclear receptor subfamily 1, group H, member 3 is a member of the nuclear hormone receptor superfamily, and has recently been shown to act as a master transcription factor governing hepatic lipogenesis in mammals. Liver X receptor alpha directly regulates both the expression of other lipogenic transcription factors and the expression of lipogenic enzymes, thereby enhancing hepatic fatty acid synthesis (FASN). In birds, like in humans, fatty acid synthesis primarily occurs in the liver. Whether LXRalpha is involved in hepatic regulation of lipogenic genes remained to be investigated in this species. Here we show that fatty acid synthase and the expression of other lipogenic genes (sterol regulatory element binding protein 1 and steroyl coenzyme A desaturase 1) are induced in chicken hepatoma cells in response to a pharmacological liver X receptor agonist, T0901317. A detailed analysis of the chicken FASN promoter revealed a functional liver X response element. These data define the chicken FASN gene as a direct target of LXRalpha and further expand the role of LXRalpha as a regulator of lipid metabolism in this species.


BMC Genomics | 2009

Using transcriptome profiling to characterize QTL regions on chicken chromosome 5

Guillaume Le Mignon; Colette Désert; Frédérique Pitel; Sophie Leroux; Olivier Demeure; Gregory Guernec; Behnam Abasht; Madeleine Douaire; Pascale Le Roy; Sandrine Lagarrigue

BackgroundAlthough many QTL for various traits have been mapped in livestock, location confidence intervals remain wide that makes difficult the identification of causative mutations. The aim of this study was to test the contribution of microarray data to QTL detection in livestock species. Three different but complementary approaches are proposed to improve characterization of a chicken QTL region for abdominal fatness (AF) previously detected on chromosome 5 (GGA5).ResultsHepatic transcriptome profiles for 45 offspring of a sire known to be heterozygous for the distal GGA5 AF QTL were obtained using a 20 K chicken oligochip. mRNA levels of 660 genes were correlated with the AF trait. The first approach was to dissect the AF phenotype by identifying animal subgroups according to their 660 transcript profiles. Linkage analysis using some of these subgroups revealed another QTL in the middle of GGA5 and increased the significance of the distal GGA5 AF QTL, thereby refining its localization. The second approach targeted the genes correlated with the AF trait and regulated by the GGA5 AF QTL region. Five of the 660 genes were considered as being controlled either by the AF QTL mutation itself or by a mutation close to it; one having a function related to lipid metabolism (HMGCS1). In addition, a QTL analysis with a multiple trait model combining this 5 gene-set and AF allowed us to refine the QTL region. The third approach was to use these 5 transcriptome profiles to predict the paternal Q versus q AF QTL mutation for each recombinant offspring and then refine the localization of the QTL from 31 cM (100 genes) at a most probable location confidence interval of 7 cM (12 genes) after determining the recombination breakpoints, an interval consistent with the reductions obtained by the two other approaches.ConclusionThe results showed the feasibility and efficacy of the three strategies used, the first revealing a QTL undetected using the whole population, the second providing functional information about a QTL region through genes related to the trait and controlled by this region (HMGCS1), the third could drastically refine a QTL region.


Gene | 2011

Regulation of LPCAT3 by LXR

Olivier Demeure; Frédéric Lecerf; Cécile Duby; Colette Désert; S. Ducheix; Hervé Guillou; Sandrine Lagarrigue

In this work we analyzed the transcriptome profiles of chicken hepatoma cells (LMH) in response to T0901317, a pharmacological agonist of the liver X receptor (LXR). Through an in silico search for LXRE (LXR response element) consensus sequences in the promoter of genes whose expression was shown to be sensitive to TO901317, we identified a LXRE in the promoter of the LPCAT3 (lysophosphatidylcholine acyltransferase 3). This motif is highly conserved between species. We further investigated the regulation of this gene and showed that the expression of LPCAT3 was induced both in chicken and human hepatoma cells (LMH and HuH-7, respectively) in response to T0901317. Transactivation and electrophoretic mobility shift assays allowed us to locate a functional LXRE in the chicken LPCAT3 promoter. Altogether these data evidence for the first time that the chicken LPCAT3 gene is a direct target of LXR and therefore suggest a new role for LXR in phospholipid homeostasis.


PLOS ONE | 2014

Re-Sequencing Data for Refining Candidate Genes and Polymorphisms in QTL Regions Affecting Adiposity in Chicken

Pierre-François Roux; Morgane Boutin; Colette Désert; Anis Djari; Diane Esquerre; Christophe Klopp; Sandrine Lagarrigue; Olivier Demeure

In this study, we propose an approach aiming at fine-mapping adiposity QTL in chicken, integrating whole genome re-sequencing data. First, two QTL regions for adiposity were identified by performing a classical linkage analysis on 1362 offspring in 11 sire families obtained by crossing two meat-type chicken lines divergently selected for abdominal fat weight. Those regions, located on chromosome 7 and 19, contained a total of 77 and 84 genes, respectively. Then, SNPs and indels in these regions were identified by re-sequencing sires. Considering issues related to polymorphism annotations for regulatory regions, we focused on the 120 and 104 polymorphisms having an impact on protein sequence, and located in coding regions of 35 and 42 genes situated in the two QTL regions. Subsequently, a filter was applied on SNPs considering their potential impact on the protein function based on conservation criteria. For the two regions, we identified 42 and 34 functional polymorphisms carried by 18 and 24 genes, and likely to deeply impact protein, including 3 coding indels and 4 nonsense SNPs. Finally, using gene functional annotation, a short list of 17 and 4 polymorphisms in 6 and 4 functional genes has been defined. Even if we cannot exclude that the causal polymorphisms may be located in regulatory regions, this strategy gives a complete overview of the candidate polymorphisms in coding regions and prioritize them on conservation- and functional-based arguments.


Genome Biology and Evolution | 2015

Expanding Duplication of Free Fatty Acid Receptor-2 (GPR43) Genes in the Chicken Genome

Camille Meslin; Colette Désert; Isabelle Callebaut; Anis Djari; Christophe Klopp; Frédérique Pitel; Sophie Leroux; Pascal Martin; Pascal Froment; Edith Guilbert; Florence Gondret; Sandrine Lagarrigue; Philippe Monget

Free fatty acid receptors (FFAR) belong to a family of five G-protein coupled receptors that are involved in the regulation of lipid metabolism, so that their loss of function increases the risk of obesity. The aim of this study was to determine the expansion of genes encoding paralogs of FFAR2 in the chicken, considered as a model organism for developmental biology and biomedical research. By estimating the gene copy number using quantitative polymerase chain reaction, genomic DNA resequencing, and RNA sequencing data, we showed the existence of 23 ± 1.5 genes encoding FFAR2 paralogs in the chicken genome. The FFAR2 paralogs shared an identity from 87.2% up to 99%. Extensive gene conversion was responsible for this high degree of sequence similarities between these genes, and this concerned especially the four amino acids known to be critical for ligand binding. Moreover, elevated nonsynonymous/synonymous substitution ratios on some amino acids within or in close-vicinity of the ligand-binding groove suggest that positive selection may have reduced the effective rate of gene conversion in this region, thus contributing to diversify the function of some FFAR2 paralogs. All the FFAR2 paralogs were located on a microchromosome in a same linkage group. FFAR2 genes were expressed in different tissues and cells such as spleen, peripheral blood mononuclear cells, abdominal adipose tissue, intestine, and lung, with the highest rate of expression in testis. Further investigations are needed to determine whether these chicken-specific events along evolution are the consequence of domestication and may play a role in regulating lipid metabolism in this species.


G3: Genes, Genomes, Genetics | 2015

Combined QTL and Selective Sweep Mappings with Coding SNP Annotation and cis-eQTL Analysis Revealed PARK2 and JAG2 as New Candidate Genes for Adiposity Regulation

Pierre-François Roux; Simon Boitard; Yuna Blum; Brian W. Parks; Alexandra Montagner; Etienne Mouisel; Anis Djari; Diane Esquerre; Colette Désert; Morgane Boutin; Sophie Leroux; Frédéric Lecerf; Elisabeth Le Bihan-Duval; Christophe Klopp; Bertrand Servin; Frédérique Pitel; Michel Jean Duclos; Hervé Guillou; Aldons J. Lusis; Olivier Demeure; Sandrine Lagarrigue

Very few causal genes have been identified by quantitative trait loci (QTL) mapping because of the large size of QTL, and most of them were identified thanks to functional links already known with the targeted phenotype. Here, we propose to combine selection signature detection, coding SNP annotation, and cis-expression QTL analyses to identify potential causal genes underlying QTL identified in divergent line designs. As a model, we chose experimental chicken lines divergently selected for only one trait, the abdominal fat weight, in which several QTL were previously mapped. Using new haplotype-based statistics exploiting the very high SNP density generated through whole-genome resequencing, we found 129 significant selective sweeps. Most of the QTL colocalized with at least one sweep, which markedly narrowed candidate region size. Some of those sweeps contained only one gene, therefore making them strong positional causal candidates with no presupposed function. We then focused on two of these QTL/sweeps. The absence of nonsynonymous SNPs in their coding regions strongly suggests the existence of causal mutations acting in cis on their expression, confirmed by cis-eQTL identification using either allele-specific expression or genetic mapping analyses. Additional expression analyses of those two genes in the chicken and mice contrasted for adiposity reinforces their link with this phenotype. This study shows for the first time the interest of combining selective sweeps mapping, coding SNP annotation and cis-eQTL analyses for identifying causative genes for a complex trait, in the context of divergent lines selected for this specific trait. Moreover, it highlights two genes, JAG2 and PARK2, as new potential negative and positive key regulators of adiposity in chicken and mice.


Comparative Biochemistry and Physiology Part D: Genomics and Proteomics | 2016

Transcriptomes of whole blood and PBMC in chickens

Colette Désert; Elodie Merlot; Tatiana Zerjal; Bertrand Bed'hom; Sonja Härtle; Aurélie Le Cam; Pierre-François Roux; E. Baéza; Florence Gondret; M. J. Duclos; Sandrine Lagarrigue

Global transcriptome analysis of chicken whole blood to discover biomarkers of different phenotypes or physiological disorders has never been investigated so far. Whole blood provides significant advantages, allowing large scale and non-invasive sampling. However, generation of gene expression data from the blood of non-mammalian species remains a challenge, notably due to the nucleated red blood cells, hindering the use of well-established protocols. The aim of this study was to analyze the relevance of using whole blood cells (WB) to find biomarkers, instead of Peripheral Blood Mononuclear Cells (PBMC), usually chosen for immune challenges. RNA sources from WB and PBMC was characterized by microarray analysis. Our results show that the quality and quantity of RNA obtained from WB was suitable for further analyses, although the quality was lower than that from PBMC. The transcriptome profiling comparison revealed that the majority of genes were expressed in both WB and PBMC. Hemoglobin subunits were the major transcripts in WB, whereas the most enriched biological process was related to protein catabolic process. Most of the over-represented transcripts in PBMC were implicated in functions specific to thrombocytes, like coagulation and platelet activation, probably due to the large proportion of this nucleated cell type in chicken PBMC. Functions related to B and T cells and to other immune functions were also enriched in the PBMC subset. We conclude that WB is more suitable for large scale immunity oriented studies and other biological processes that have been poorly investigated so far.


Genetics Selection Evolution | 2017

Long noncoding RNA repertoire in chicken liver and adipose tissue

Kévin Muret; Christophe Klopp; Valentin Wucher; Diane Esquerré; Fabrice Legeai; Frédéric Lecerf; Colette Désert; Morgane Boutin; Frédéric Jehl; Hervé Acloque; Elisabetta Giuffra; Sarah Djebali; Sylvain Foissac; Thomas Derrien; Sandrine Lagarrigue


BMC Genomics | 2011

Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken

Yuna Blum; Guillaume Le Mignon; David Causeur; Olivier Filangi; Colette Désert; Olivier Demeure; Pascale Le Roy; Sandrine Lagarrigue

Collaboration


Dive into the Colette Désert's collaboration.

Top Co-Authors

Avatar

Sandrine Lagarrigue

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Christophe Klopp

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Frédéric Lecerf

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Pierre-François Roux

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Anis Djari

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Diane Esquerre

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

M. J. Duclos

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Frédérique Pitel

Institut national de la recherche agronomique

View shared research outputs
Top Co-Authors

Avatar

Marco Moroldo

Institut national de la recherche agronomique

View shared research outputs
Researchain Logo
Decentralizing Knowledge