Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens.

BACKGROUND: To reduce the cost of genomic selection, a low-density (LD) single nucleotide polymorphism (SNP) chip can be used in combination with imputation for genotyping selection candidates instead of using a high-density (HD) SNP chip. Next-generation sequencing (NGS) techniques have been increasingly used in livestock species but remain expensive for routine use for genomic selection. An alternative and cost-efficient solution is to use restriction site-associated DNA sequencing (RADseq) techniques to sequence only a fraction of the genome using restriction enzymes. From this perspective, use of RADseq techniques followed by an imputation step on HD chip as alternatives to LD chips for genomic selection was studied in a pure layer line. RESULTS: Genome reduction and sequencing fragments were identified on reference genome using four restriction enzymes (EcoRI, TaqI, AvaII and PstI) and a double-digest RADseq (ddRADseq) method (TaqI-PstI). The SNPs contained in these fragments were detected from the 20X sequence data of the individuals in our population. Imputation accuracy on HD chip with these genotypes was assessed as the mean correlation between true and imputed genotypes. Several production traits were evaluated using single-step GBLUP methodology. The impact of imputation errors on the ranking of the selection candidates was assessed by comparing a genomic evaluation based on ancestry using true HD or imputed HD genotyping. The relative accuracy of genomic estimated breeding values (GEBVs) was investigated by considering the GEBVs estimated on offspring as a reference. With AvaII or PstI and ddRADseq with TaqI and PstI, more than 10 K SNPs were detected in common with the HD SNP chip, resulting in an imputation accuracy greater than 0.97. The impact of imputation errors on genomic evaluation of the breeders was reduced, with a Spearman correlation greater than 0.99. Finally, the relative accuracy of GEBVs was equivalent. CONCLUSIONS: RADseq approaches can be interesting alternatives to low-density SNP chips for genomic selection. With more than 10 K SNPs in common with the SNPs of the HD SNP chip, good imputation and genomic evaluation results can be obtained. However, with real data, heterogeneity between individuals with missing data must be considered.

RNA-Seq transcriptome data of the liver of common Pekin, Muscovy, mule and Hinny ducks fed ad libitum or overfed.

Duck species are known to have different ability to fatty liver production in response to overfeeding and gene expression analyses can help to characterize mechanisms involved in these differences. This data article reports the sequencing of RNAs extracted from the liver of Pekin and Muscovy duck species and of their reciprocal hybrids, Mule and Hinny ducks fed ad libitum or overfed. Libraries were prepared by selecting polyadenylated mRNAs and RNA Sequencing (RNASeq) was performed using Illumina HiSeq2000 platform. RNASeq data presented in this article were deposited in the NCBI sequence read archive (SRA) under the accession number SRP144764 and links to these data were also indicated in the Data INRAE repository (https://doi.org/10.15454/JJZ3QQ). Transcriptome analyses of these data were published in Hérault et al. (2019) and Liu et al. (2020).

Development of a relevant strategy using de novo transcriptome assembly method for transcriptome comparisons between Muscovy and common duck species and their reciprocal inter-specific mule and hinny hybrids fed ad libitum and overfed.

BACKGROUND: Common Pekin and Muscovy ducks and their intergeneric hinny and mule hybrids have different abilities for fatty liver production. RNA-Seq analyses from the liver of these different genetic types fed ad libitum or overfed would help to identify genes with different response to overfeeding between them. However RNA-seq analyses from different species and comparison is challenging. The goal of this study was develop a relevant strategy for transcriptome analysis and comparison between different species. RESULTS: Transcriptomes were first assembled with a reference-based approach. Important mapping biases were observed when heterologous mapping were conducted on common duck reference genome, suggesting that this reference-based strategy was not suited to compare the four different genetic types. De novo transcriptome assemblies were then performed using Trinity and Oases. Assemblies of transcriptomes were not relevant when more than a single genetic type was considered. Finally, single genetic type transcriptomes were assembled with DRAP in a mega-transcriptome. No bias was observed when reads from the different genetic types were mapped on this mega-transcriptome and differences in gene expression between the four genetic types could be identified. CONCLUSIONS: Analyses using both reference-based and de novo transcriptome assemblies point out a good performance of the de novo approach for the analysis of gene expression in different species. It also allowed the identification of differences in responses to overfeeding between Pekin and Muscovy ducks and hinny and mule hybrids.

Interest of using imputation for genomic evaluation in layer chicken.

With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers. But to routinely implement this solution, the impact of imputation on genomic evaluation accuracy must be studied. It is also interesting to study the consequences of the use of low-density SNP chips in genomic evaluation accuracy. In this perspective, the interest of using imputation in genomic selection was studied in a pure layer line. Two low-density SNP chip designs were compared: an equidistant methodology and a methodology based on linkage disequilibrium. Egg weight, egg shell color, egg shell strength, and albumen height were evaluated with single-step genomic best linear unbiased prediction methodology. The impact of imputation errors or the absence of imputation on the ranking of the male selection candidates was assessed with a genomic evaluation based on ancestry. Thus, genomic estimated breeding values (GEBV) obtained with imputed HD genotypes or low-density genotypes were compared with GEBV obtained with the HD SNP chip. The relative accuracy of GEBV was also investigated by considering as reference GEBV estimated on the offspring. A limited reordering of the breeders, selected on a multitrait index, was observed. Spearman correlations between GEBV on HD genotypes and GEBV on low-density genotypes (with or without imputation) were always higher than 0.94 with more than 3K SNP. For the genetically closer, top 150 individuals for a specific trait, with imputation, the reordering was reduced with correlation higher than 0.94 with more than 3K SNP. Without imputation, the correlations remained lower than 0.85 with less than 3K and 16K SNP for equidistant and linkage disequilibrium methodology, respectively. The differences in GEBV correlations between both methodologies were never significant. The conclusions were the same for all studied traits.

Reliability of genomic evaluation for egg quality traits in layers.

BACKGROUND: Genomic evaluation, based on the use of thousands of genetic markers in addition to pedigree and phenotype information, has become the standard evaluation methodology in dairy cattle breeding programmes over the past several years. Despite the many differences between dairy cattle breeding and poultry breeding, genomic selection seems very promising for the avian sector, and studies are currently being conducted to optimize avian selection schemes. In this optimization perspective, one of the key parameters is to properly predict the accuracy of genomic evaluation in pure line layers. RESULTS: It was observed that genomic evaluation, whether performed on males or females, always proved more accurate than genetic evaluation. The gain was higher when phenotypic information was narrowed, and an augmentation of the size of the reference population led to an increase in accuracy prediction with regard to genomic evaluation. By taking into account the increase of selection intensity and the decrease of the generation interval induced by genomic selection, the expected annual genetic gain would be higher with ancestry-based genomic evaluation of male candidates than with genetic evaluation based on collaterals. This advantage of genomic selection over genetic selection requires more detailed further study for female candidates. CONCLUSIONS: In conclusion, in the population studied, the genomic evaluation of egg quality traits of breeding birds at birth seems to be a promising strategy, at least for the selection of males.

Designer benzodiazepines' pharmacological effects and potencies: How to find the information.

BACKGROUND: Scientific data on the psychopharmacological effects of new psychoactive substances (NPSs) are scarce. Web fora contain a wealth of information posted by users as trip reports (TRs), but the reliability of the reports remains questionable because of the nature of the used molecule and the potential for dose inaccuracies. We focused on the TRs of designer benzodiazepine (DBZD) users since their psychopharmacological effects are similar to prescription benzodiazepines (BZDs). Moreover, the impact of functional groups on the BZD rings with regards to the potency has been fairly/quite studied, allowing structural analysis. METHODS: DBZDs offering more than 15 TRs with at least two accounts on experienced effects were included. Data were analyzed with the empirical phenomenological psychological method. Reported effects were analyzed and the pharmacological potencies of DBZDs were compared by calculating a 'potency score'. RESULTS: In total, 197 TRs for clonazolam, deschloroetizolam, diclazepam, etizolam, flubromazepam, flubromazolam, meclonazepam, metizolam, nifoxipam and pyrazolam were analyzed. Effects similar to prescription BZDs were reported for all the selected DBZDs. Pyrazolam was reported to be the most anxiolytic DBZD, flubromazolam the most hypnotic, etizolam the most euphoric and flubromazolam and clonazolam as the most amnesic DBZDs. Diclazepam and pyrazolam were not reported to induce euphoria. Flubromazepam, flubromazolam, clonazolam and meclonazepam were the most potent and deschloroetizolam, nifoxipam, metizolam and pyrazolam the least potent. The chemical structure of the different DBZDs and the functional groups on the BZD rings confirmed this ranking, except for nifoxipam. CONCLUSIONS: When information on NPSs obtained from Internet fora are abundant, it could be considered as an appreciable data source.

RNA-seq analysis of hepatic gene expression of common Pekin, Muscovy, mule and hinny ducks fed ad libitum or overfed.

BACKGROUND: Duck species are known to have different susceptibility to fatty liver production in response to overfeeding. In order to better describe mechanisms involved in the development of hepatic steatosis and differences between species, transcriptome analyses were conducted on RNAs extracted from the livers of Pekin and Muscovy duck species and of their reciprocal hybrids, Mule and Hinny ducks fed ad libitum or overfed to identify differentially expressed genes and associated functions. RESULTS: After extraction from the liver of ducks from the four genetic types, RNAs were sequenced and sequencing data were analyzed. Hierarchic clustering and principal component analyses of genes expression levels indicated that differences between individuals lie primarily in feeding effect, differences between genetic types being less important. However, Muscovy ducks fed ad libitum and overfed were clustered together. Interestingly, Hinny and Mule hybrid ducks could not be differentiated from each other, according to feeding. Many genes with expression differences between overfed and ad libitum fed ducks were identified in each genetic type. Functional annotation analyses of these differentially expressed genes highlighted some expected functions (carbohydrate and lipid metabolisms) but also some unexpected ones (cell proliferation and immunity). CONCLUSIONS: These analyses evidence differences in response to overfeeding between different genetic types and help to better characterize functions involved in hepatic steatosis in ducks.

Design of low density SNP chips for genotype imputation in layer chicken.

BACKGROUND: The main goal of selection is to achieve genetic gain for a population by choosing the best breeders among a set of selection candidates. Since 2013, the use of a high density genotyping chip (600K Affymetrix® Axiom® HD genotyping array) for chicken has enabled the implementation of genomic selection in layer and broiler breeding, but the genotyping costs remain high for a routine use on a large number of selection candidates. It has thus been deemed interesting to develop a low density genotyping chip that would induce lower costs. In this perspective, various simulation studies have been conducted to find the best way to select a set of SNPs for low density genotyping of two laying hen lines. RESULTS: To design low density SNP chips, two methodologies, based on equidistance (EQ) or on linkage disequilibrium (LD) were compared. Imputation accuracy was assessed as the mean correlation between true and imputed genotypes. The results showed correlations more sensitive to false imputation of SNPs having low Minor Allele Frequency (MAF) when the EQ methodology was used. An increase in imputation accuracy was obtained when SNP density was increased, either through an increase in the number of selected windows on a chromosome or through the rise of the LD threshold. Moreover, the results varied depending on the type of chromosome (macro or micro-chromosome). The LD methodology enabled to optimize the number of SNPs, by reducing the SNP density on macro-chromosomes and by increasing it on micro-chromosomes. Imputation accuracy also increased when the size of the reference population was increased. Conversely, imputation accuracy decreased when the degree of kinship between reference and candidate populations was reduced. Finally, adding selection candidates' dams in the reference population, in addition to their sire, enabled to get better imputation results. CONCLUSIONS: Whichever the SNP chip, the methodology, and the scenario studied, highly accurate imputations were obtained, with mean correlations higher than 0.83. The key point to achieve good imputation results is to take into account chicken lines' LD when designing a low density SNP chip, and to include the candidates' direct parents in the reference population.

Combined GWAS and LDLA approaches to improve genome-wide quantitative trait loci detection affecting carcass and meat quality traits in pig.

Many QTL affecting meat quality and carcass traits have been reported. However, in most of the cases these QTL have been detected in non-commercial populations. Therefore, a family structured population of 457 F2 pigs issued from an inter-cross between 2 commercial sire lines was used to detect QTL affecting meat quality and carcass traits. All animals were genotyped using the Illumina PorcineSNP60 BeadChip platform. Genome-wide association studies were used in combination with linkage disequilibrium-linkage analysis to identify QTL. A total of 32 QTL were detected. Nine of these QTL exceeded the genome-wide 5% significance threshold. We detected 18 QTL affecting carcass composition traits and 16 QTL affecting meat quality traits. Using post-QTL bioinformatics analysis we highlighted 26 functional candidate genes related to fatness, muscle development, meat color and meat pH. Finally, our results shed light on the advantage of using different QTL detection methodologies to get a global overview of the QTL present in the studied population.

Genome-wide association study and biological pathway analysis of the Eimeria maxima response in broilers.

BACKGROUND: Coccidiosis is the most common and costly disease in the poultry industry and is caused by protozoans of the Eimeria genus. The current control of coccidiosis, based on the use of anticoccidial drugs and vaccination, faces serious obstacles such as drug resistance and the high costs for the development of efficient vaccines, respectively. Therefore, the current control programs must be expanded with complementary approaches such as the use of genetics to improve the host response to Eimeria infections. Recently, we have performed a large-scale challenge study on Cobb500 broilers using E. maxima for which we investigated variability among animals in response to the challenge. As a follow-up to this challenge study, we performed a genome-wide association study (GWAS) to identify genomic regions underlying variability of the measured traits in the response to Eimeria maxima in broilers. Furthermore, we conducted a post-GWAS functional analysis to increase our biological understanding of the underlying response to Eimeria maxima challenge. RESULTS: In total, we identified 22 single nucleotide polymorphisms (SNPs) with q value <0.1 distributed across five chromosomes. The highly significant SNPs were associated with body weight gain (three SNPs on GGA5, one SNP on GGA1 and one SNP on GGA3), plasma coloration measured as optical density at wavelengths in the range 465-510 nm (10 SNPs and all on GGA10) and the percentage of ß2-globulin in blood plasma (15 SNPs on GGA1 and one SNP on GGA2). Biological pathways related to metabolic processes, cell proliferation, and primary innate immune processes were among the most frequent significantly enriched biological pathways. Furthermore, the network-based analysis produced two networks of high confidence, with one centered on large tumor suppressor kinase 1 (LATS1) and 2 (LATS2) and the second involving the myosin heavy chain 6 (MYH6). CONCLUSIONS: We identified several strong candidate genes and genomic regions associated with traits measured in response to Eimeria maxima in broilers. Furthermore, the post-GWAS functional analysis indicates that biological pathways and networks involved in tissue proliferation and repair along with the primary innate immune response may play the most important role during the early stage of Eimeria maxima infection in broilers.

GWAS analyses reveal QTL in egg layers that differ in response to diet differences.

BACKGROUND: The genetic architecture of egg production and egg quality traits, i.e. the quantitative trait loci (QTL) that influence these traits, is still poorly known. To date, 33 studies have focused on the detection of QTL for laying traits in chickens, but less than 10 genes have been identified. The availability of a high-density SNP (single nucleotide polymorphism) chicken array developed by Affymetrix, i.e. the 600K Affymetrix(®) Axiom(®) HD genotyping array offers the possibility to narrow down the localization of previously detected QTL and to detect new QTL. This high-density array is also anticipated to take research beyond the classical hypothesis of additivity of QTL effects or of QTL and environmental effects. The aim of our study was to search for QTL that influence laying traits using the 600K SNP chip and to investigate whether the effects of these QTL differed between diets and age at egg collection. RESULTS: One hundred and thirty-one QTL were detected for 16 laying traits and were spread across all marked chromosomes, except chromosomes 16 and 25. The percentage of variance explained by a QTL varied from 2 to 10 % for the various traits, depending on diet and age at egg collection. Chromosomes 3, 9, 10 and Z were overrepresented, with more than eight QTL on each one. Among the 131 QTL, 60 had a significantly different effect, depending on diet or age at egg collection. For egg production traits, when the QTL × environment interaction was significant, numerous inversions of sign of the SNP effects were observed, whereas for egg quality traits, the QTL × environment interaction was mostly due to a difference of magnitude of the SNP effects. CONCLUSIONS: Our results show that numerous QTL influence egg production and egg quality traits and that the genomic regions, which are involved in shaping the ability of layer chickens to adapt to their environment for egg production, vary depending on the environmental conditions. The next question will be to address what the impact of these genotype × environment interactions is on selection.

The Longissimus and Semimembranosus muscles display marked differences in their gene expression profiles in pig.

BACKGROUND: Meat quality depends on skeletal muscle structure and metabolic properties. While most studies carried on pigs focus on the Longissimus muscle (LM) for fresh meat consumption, Semimembranosus (SM) is also of interest because of its importance for cooked ham production. Even if both muscles are classified as glycolytic muscles, they exhibit dissimilar myofiber composition and metabolic characteristics. The comparison of LM and SM transcriptome profiles undertaken in this study may thus clarify the biological events underlying their phenotypic differences which might influence several meat quality traits. METHODOLOGY/PRINCIPAL FINDINGS: Muscular transcriptome analyses were performed using a custom pig muscle microarray: the 15 K Genmascqchip. A total of 3823 genes were differentially expressed between the two muscles (Benjamini-Hochberg adjusted P value ≤0.05), out of which 1690 and 2133 were overrepresented in LM and SM respectively. The microarray data were validated using the expression level of seven differentially expressed genes quantified by real-time RT-PCR. A set of 1047 differentially expressed genes with a muscle fold change ratio above 1.5 was used for functional characterization. Functional annotation emphasized five main clusters associated to transcriptome muscle differences. These five clusters were related to energy metabolism, cell cycle, gene expression, anatomical structure development and signal transduction/immune response. CONCLUSIONS/SIGNIFICANCE: This study revealed strong transcriptome differences between LM and SM. These results suggest that skeletal muscle discrepancies might arise essentially from different post-natal myogenic activities.

Comparison of muscle transcriptome between pigs with divergent meat quality phenotypes identifies genes related to muscle metabolism and structure.

BACKGROUND: Meat quality depends on physiological processes taking place in muscle tissue, which could involve a large pattern of genes associated with both muscle structural and metabolic features. Understanding the biological phenomena underlying muscle phenotype at slaughter is necessary to uncover meat quality development. Therefore, a muscle transcriptome analysis was undertaken to compare gene expression profiles between two highly contrasted pig breeds, Large White (LW) and Basque (B), reared in two different housing systems themselves influencing meat quality. LW is the most predominant breed used in pig industry, which exhibits standard meat quality attributes. B is an indigenous breed with low lean meat and high fat contents, high meat quality characteristics, and is genetically distant from other European pig breeds. METHODOLOGY/PRINCIPAL FINDINGS: Transcriptome analysis undertaken using a custom 15 K microarray, highlighted 1233 genes differentially expressed between breeds (multiple-test adjusted P-value<0.05), out of which 635 were highly expressed in the B and 598 highly expressed in the LW pigs. No difference in gene expression was found between housing systems. Besides, expression level of 12 differentially expressed genes quantified by real-time RT-PCR validated microarray data. Functional annotation clustering emphasized four main clusters associated to transcriptome breed differences: metabolic processes, skeletal muscle structure and organization, extracellular matrix, lysosome, and proteolysis, thereby highlighting many genes involved in muscle physiology and meat quality development. CONCLUSIONS/SIGNIFICANCE: Altogether, these results will contribute to a better understanding of muscle physiology and of the biological and molecular processes underlying meat quality. Besides, this study is a first step towards the identification of molecular markers of pork quality and the subsequent development of control tools.

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs.

BACKGROUND: Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. RESULTS: Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. CONCLUSIONS: Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs.

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.