Using transcriptome profiling to characterize QTL regions on chicken chromosome 5.

BACKGROUND: Although 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). RESULTS: Hepatic 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. CONCLUSION: The 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.

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

BACKGROUND: Starvation 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. RESULTS: A 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). CONCLUSION: This 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.

Microarray analysis of differential gene expression in the liver of lean and fat chickens.

Excessive adiposity has become a major drawback in meat-type chicken production. However, few studies were conducted to analyze the liver expression of genes involved in pathways and mechanisms leading to adiposity. A previous study performed by differential display on RNAs extracted from chicken livers from lean and fat lines allowed us to isolate cDNA products of genes with putative differential expression. In this study, a cDNA microarray resource was developed from these products together with cDNAs from genes involved in or related to lipid metabolism. This resource was used to analyze gene expression in the liver from lean and fat chickens. Some genes were found with a difference in expression between lean and fat animals and/or correlated to adipose tissue weight. Cytochrome P450 2C45, thought to play a role in biotransformation of steroids and poly-unsaturated fatty acids, was more expressed in lean chickens whereas fatty acid synthase, stearoyl-CoA desaturase, sterol response element binding factor 1 and hepatocyte nuclear factor 4, respectively involved in lipogenesis and its regulation, were more expressed in fat chickens. These results indicate that mechanisms involved in the expression and regulation of lipogenic genes could play a key role in fatness ontogenesis in chickens from lean and fat lines.

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

BACKGROUND: The 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. RESULTS: A 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. CONCLUSION: The 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.

Differential expression and genetic variation of hepatic messenger RNAs from genetically lean and fat chickens.

Although excessive adiposity has become a major drawback in meat type chicken production, few of the genes involved in this process have been characterized so far. In order to identify putative genes involved in adiposity, we performed differential display analysis of RNAs extracted from the liver of divergently selected lean and fat chickens. Twenty-six differential products were selected and purified by single strand conformation polymorphism gel electrophoresis before sequencing and Northern blot analyses. An orthologous sequence of a mammalian cytochrome P450 2C subfamily member was proven to be differentially expressed in the liver of lean and fat chickens and could play an important role in the regulation of adiposity. In mammals, these genes are involved in detoxification of xenobiotics and metabolism of some important biological compounds. Four other genes were found differentially expressed to a lower extent. Some unidentified products were shown to be lean or fat specific, with sequence polymorphism and liver specific expression, strongly suggesting that the related gene could be directly involved in adiposity. Our data indicate that differential display can evidence genes with differential expression and with sequence polymorphism, making this strategy more accurate for differential analysis of messenger RNAs.

Genetic linkage and expression analysis of SREBP and lipogenic genes in fat and lean chicken.

To identify the genes directly responsible, through DNA polymorphism, for the difference in fatness observed between a lean and a fat chicken line, we studied five genes (ACL, ACC, FAS, ME, SCD1) encoding key enzymes involved in liver fatty acid synthesis and secretion. Genetic linkage was tested between polymorphic sites in the genes and the fatness trait segregating in an F2 design obtained by inter-crossing the two fat and lean lines. Despite a confirmation of a higher mRNA level in the fat birds, no genetic linkage of the gene alleles with the phenotype could be found. As a test of the implication of upstream regulatory transcription factors, SREPB genes were also studied. The lack of genetic linkage of SREBP genes with fatness shows that these genes are not directly responsible through polymorphism for fatness variability in our model. Moreover, the similar SREBP mRNA levels observed between the two lines led us to exclude also transcriptional factors regulating the two SREBP genes as being directly responsible for fatness variability. However, the genes involved in post-translational modifications of SREBPs remain candidates to investigate. These results emphasised the interest to perform expression and genetic linkage studies jointly, to progress in identifying the genetic origin of variability of a quantitative trait.

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.

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.