Madeleine Douaire

Mapping quantitative trait loci affecting fatness and breast muscle weight in meat-type chicken lines divergently selected on abdominal fatness

Quantitative trait loci (QTL) for abdominal fatness and breast muscle weight were investigated in a three-generation design performed by inter-crossing two experimental meat-type chicken lines that were divergently selected on abdominal fatness. A total of 585 F2 male offspring from 5 F1 sires and 38 F1 dams were recorded at 8 weeks of age for live body, abdominal fat and breast muscle weights. One hundred-twenty nine microsatellite markers, evenly located throughout the genome and heterozygous for most of the F1 sires, were used for genotyping the F2 birds. In each sire family, those offspring exhibiting the most extreme values for each trait were genotyped. Multipoint QTL analyses using maximum likelihood methods were performed for abdominal fat and breast muscle weights, which were corrected for the effects of 8-week body weight, dam and hatching group. Isolated markers were assessed by analyses of variance. Two significant QTL were identified on chromosomes 1 and 5 with effects of about one within-family residual standard deviation. One breast muscle QTL was identified on GGA1 with an effect of 2.0 within-family residual standard deviation.

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

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.

Fatness QTL on chicken chromosome 5 and interaction with sex

Quantitative trait loci (QTL) affecting fatness in male chickens were previously identified on chromosome 5 (GGA5) in a three-generation design derived from two experimental chicken lines divergently selected for abdominal fat weight. A new design, established from the same pure lines, produced 407 F2 progenies (males and females) from 4 F1-sire families. Body weight and abdominal fat were measured on the F2 at 9 wk of age. In each sire family, selective genotyping was carried out for 48 extreme individuals for abdominal fat using seven microsatellite markers from GGA5. QTL analyses confirmed the presence of QTL for fatness on GGA5 and identified a QTL by sex interaction. By crossing one F1 sire heterozygous at the QTL with lean line dams, three recombinant backcross 1 (BC1) males were produced and their QTL genotypes were assessed in backcross 2 (BC2) progenies. These results confirmed the QTL by sex interaction identified in the F2 generation and they allow mapping of the female QTL to less than 8 Mb at the distal part of the GGA5. They also indicate that fat QTL alleles were segregating in both fat and lean lines.

A high-resolution radiation hybrid map of chicken chromosome 5 and comparison with human chromosomes

BackgroundThe resolution of radiation hybrid (RH) maps is intermediate between that of the genetic and BAC (Bacterial Artificial Chromosome) contig maps. Moreover, once framework RH maps of a genome have been constructed, a quick location of markers by simple PCR on the RH panel is possible. The chicken ChickRH6 panel recently produced was used here to construct a high resolution RH map of chicken GGA5. To confirm the validity of the map and to provide valuable comparative mapping information, both markers from the genetic map and a high number of ESTs (Expressed Sequence Tags) were used. Finally, this RH map was used for testing the accuracy of the chicken genome assembly for chromosome 5.ResultsA total of 169 markers (21 microsatellites and 148 ESTs) were typed on the ChickRH6 RH panel, of which 134 were assigned to GGA5. The final map is composed of 73 framework markers extending over a 1315.6 cR distance. The remaining 61 markers were placed alongside the framework markers within confidence intervals.ConclusionThe high resolution framework map obtained in this study has markers covering the entire chicken chromosome 5 and reveals the existence of a high number of rearrangements when compared to the human genome. Only two discrepancies were observed in relation to the sequence assembly recently reported for this chromosome.

Using transcriptome profiling to characterize QTL regions on chicken chromosome 5

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.

Mapping of FASN and ACACA on two chicken microchromosomes disrupts the human 17q syntenic group well conserved in mammals

Fatty acid synthase and Acetyl-CoA carboxylase are both key enzymes of lipogenesis and may play a crucial role in the weight variability of abdominal adipose tissue in the growing chicken. They are encoded by the FASN and ACACA genes, located on human Chromosome (Chr) 17q25 and on Chr 17q12 or 17q21 respectively, a large region of conserved synteny among mammals. We have localized the homologous chicken genes FASN and ACACA coding for these enzymes, by single-strand conformation polymorphism analysis on different linkage groups of the Compton and East Lansing consensus genetic maps and by FISH on two different chicken microchromosomes. Although synteny is not conserved between these two genes, our results revealed linkage in chicken between FASN and NDPK (nucleoside diphosphate kinase), a homolog to the human NME1 and NME2 genes (non-metastatic cell proteins 1 and 2), both located on human Chr 17q21.3, and also between FASN and H3F3B (H3 histone family 3B), located on human Chr 17q25. The analysis of mapping data from the literature for other chicken and mammalian genes indicates rearrangements have occurred in this region in the mammalian lineage since the mammalian and avian radiation.

Effet du gène Na (cou nu) chez des coqs élevés à deux températures. II. Caractéristiques du sperme et reproduction

(plumage normal) issus de l’accouplement de parents tous deux hétérozygotes Nana +, appartenant à une même population expérimentale, ont été répartis en 2 groupes maintenus l’un à une température constante de 30 °C, l’autre à 18 °C obtenus progressivement après l’âge de 3 semaines. Les coqs, au nombre total de 256, étaient élevés au sol jusqu’à 10 semaines puis en cages individuelles. Sur chacun étaient mesurés à 3 âges (19, 23, 27 semaines) des caractéristiques du sperme (volume, concentration, nombre de spermatozoïdes par éjaculat, motilité). L’âge au ïer éjaculat était aussi noté individuellement ainsi que le taux de testostérone plasmatique à 27 semaines. D’autre part, à l’âge de 21 et 28 semaines et sur un échantillon de 24 groupes de 5 coqs (4 par génotype et traitement) dont le sperme était mélangé, des paramètres biochimiques du liquide séminal ou des spermatozoïdes étaient dosés.

Interaction génotype-milieu et modèle mixte. I. Modélisation

où w’‘ représente l’effet moyen de la modalité k du facteur milieu; A, représente l’effet aléatoire du facteur père; B-! représente l’effet aléatoire du facteur mère intra père; 0) représente l’interaction aléatoire (père, mère) x milieu. Ce modèle résulte d’une procédure d’échantillonnage qui rend aléatoires les effets génétiques; il nous donne des espérances et covariances dépendantes du milieu. L’introduction de conditions supplémentaires entraîne des liaisons entre les covariances.

Effet du gène Na (cou nu) chez des coqs élevés à deux températures. I. Croissance, consommation alimentaire et caractéristiques physiologiques

Deux cent cinquante-six coqs des génotypes Na Na, Na na’ et na’ na’ ont été comparés pour leurs performances de croissance, leur consommation alimentaire et des caractéristiques morphologiques et physiologiques, soit à la température ambiante de 18 °C à partir de l’âge de 9 semaines, soit à 30 °C. Au total, la température de 30 °C, par comparaison à 18 °C, diminue la consommation alimentaire, le poids vif, le rythme respiratoire, l’hématocrite, et augmente la croissance des