Circadian clock mechanism driving mammalian photoperiodism.

The annual photoperiod cycle provides the critical environmental cue synchronizing rhythms of life in seasonal habitats. In 1936, Bünning proposed a circadian-based coincidence timer for photoperiodic synchronization in plants. Formal studies support the universality of this so-called coincidence timer, but we lack understanding of the mechanisms involved. Here we show in mammals that long photoperiods induce the circadian transcription factor BMAL2, in the pars tuberalis of the pituitary, and triggers summer biology through the eyes absent/thyrotrophin (EYA3/TSH) pathway. Conversely, long-duration melatonin signals on short photoperiods induce circadian repressors including DEC1, suppressing BMAL2 and the EYA3/TSH pathway, triggering winter biology. These actions are associated with progressive genome-wide changes in chromatin state, elaborating the effect of the circadian coincidence timer. Hence, circadian clock-pituitary epigenetic pathway interactions form the basis of the mammalian coincidence timer mechanism. Our results constitute a blueprint for circadian-based seasonal timekeeping in vertebrates.

Diurnal and photoperiodic changes in thyrotrophin-stimulating hormone ß expression and associated regulation of deiodinase enzymes (DIO2, DIO3) in the female juvenile chicken hypothalamus.

Increased thyrotrophin-stimulating hormone ß (TSHß) expression in the pars tuberalis is assumed to be an early step in the neuroendocrine mechanism transducing photoperiodic information. The present study aimed to determine the relationship between long-photoperiod (LP) and diurnal TSHß gene expression in the juvenile chicken by comparing LP-photostimulated birds with groups kept on a short photoperiod (SP) for 1 or 12 days. TSHß expression increased by 3- and 23-fold after 1 and 12 days of LP-photostimulation both during the day and at night. Under both SP and LP conditions, TSHß expression was between 3- and 14-fold higher at night than in the day, suggesting that TSHß expression cycles in a diurnal pattern irrespective of photoperiod. The ratio of DIO2/3 was decreased on LPs, consequent to changes in DIO3 expression, although there was no evidence of any diurnal effect on DIO2 or DIO3 expression. Plasma prolactin concentrations revealed both an effect of LPs and time-of-day. Thus, TSHß expression changes in a dynamic fashion both diurnally and in response to photoperiod.

Commercial chicken breeds exhibit highly divergent patterns of linkage disequilibrium.

The analysis of linkage disequilibrium (LD) underpins the development of effective genotyping technologies, trait mapping and understanding of biological mechanisms such as those driving recombination and the impact of selection. We apply the Malécot-Morton model of LD to create additive LD maps that describe the high-resolution LD landscape of commercial chickens. We investigated LD in chickens (Gallus gallus) at the highest resolution to date for broiler, white egg and brown egg layer commercial lines. There is minimal concordance between breeds of fine-scale LD patterns (correlation coefficient <0.21), and even between discrete broiler lines. Regions of LD breakdown, which may align with recombination hot spots, are enriched near CpG islands and transcription start sites (P<2.2 × 10-16), consistent with recent evidence described in finches, but concordance in hot spot locations between commercial breeds is only marginally greater than random. As in other birds, functional elements in the chicken genome are associated with recombination but, unlike evidence from other bird species, the LD landscape is not stable in the populations studied. The development of optimal genotyping panels for genome-led selection programmes will depend on careful analysis of the LD structure of each line of interest. Further study is required to fully elucidate the mechanisms underlying highly divergent LD patterns found in commercial chickens.

Animal genomics and infectious disease resistance in poultry.

Avian pathogens are responsible for major costs to society, both in terms of huge economic losses to the poultry industry and their implications for human health. The health and welfare of millions of birds is under continued threat from many infectious diseases, some of which are increasing in virulence and thus becoming harder to control, such as Marek's disease virus and avian influenza viruses. The current era in animal genomics has seen huge developments in both technologies and resources, which means that researchers have never been in a better position to investigate the genetics of disease resistance and determine the underlying genes/mutations which make birds susceptible or resistant to infection. Avian genomics has reached a point where the biological mechanisms of infectious diseases can be investigated and understood in poultry and other avian species. Knowledge of genes conferring disease resistance can be used in selective breeding programmes or to develop vaccines which help to control the effects of these pathogens, which have such a major impact on birds and humans alike.

Les agents pathogènes affectant les espèces aviaires représentent un coût majeur pour la société du fait des pertes économiques colossales qu'ils font subir à la filière avicole et de leurs effets sur la santé publique. Un certain nombre de maladies infectieuses font peser une menace permanente sur la santé et le bien-être de millions d'oiseaux ; parmi les agents pathogènes en cause, certains gagnent en virulence et deviennent donc de plus en plus difficiles à contrôler ; c'est le cas par exemple du virus de la maladie de Marek et des virus de la grippe aviaire. L'ère actuelle de la génomique animale se caractérise par des avancées considérables au plan technologique et par des ressources accrues, les chercheurs bénéficiant aujourd'hui d'atouts sans précédent pour élucider la génétique de la résistance aux maladies et pour déterminer les gènes et les mutations régissant la sensibilité ou la résistance des oiseaux à une infection. La génomique aviaire a atteint un niveau permettant d'étudier et de comprendre les mécanismes biologiques des maladies infectieuses chez les volailles et d'autres espèces aviaires. La connaissance des gènes codant pour la résistance aux maladies permet de concevoir des programmes de sélection et de mettre au point des vaccins destinés à contrôler les effets induits par des agents pathogènes à fort impact sur les oiseaux ou l'être humain.

Los patógenos aviares entrañan importantes costos para la sociedad, tanto por las enormes pérdidas económicas que infligen al sector avícola como por sus efectos sobre la salud humana. La salud y el bienestar de millones de aves se encuentran bajo la amenaza constante de muchas enfermedades infecciosas, algunos de cuyos agentes cobran cada vez mayor virulencia y resultan por ello cada vez más difíciles de combatir, como ocurre con los virus de la enfermedad de Marek o de la influenza aviar. La genómica animal conoce ahora mismo un auge extraordinario, desde el doble punto de vista de la tecnología y de los recursos, lo que significa que los investigadores nunca han estado en mejor posición para estudiar los mecanismos genéticos de la resistencia a las enfermedades y determinar los genes y/o mutaciones que subyacen a la sensibilidad o la resistencia de las aves a una infección. La genómica aviar ha alcanzado un punto en el que ya es posible investigar y comprender los mecanismos biológicos de las enfermedades infecciosas de aves de corral y otras especies aviares. Ahora cabe utilizar el conocimiento de los genes que confieren resistencia como parte de programas de selección reproductiva o para obtener vacunas que ayuden a combatir los efectos de esos patógenos, que tan perjudiciales resultan para aves y personas por un igual.

Quantitative trait loci with sex-specific effects for internal organs weights and hematocrit value in a broiler-layer cross.

Rapid growth in broilers is associated with susceptibility to metabolic disorders such as pulmonary hypertension syndrome (ascites) and sudden death. This study describes a genome search for QTL associated with relative weight of cardio respiratory and metabolically important organs (heart, lungs, liver and gizzard), and hematocrit value in a Brazilian broiler-layer cross. QTL with similar or different effects across sexes were investigated. At 42 days of age after fasted for 6 h, the F2 chickens were weighed and slaughtered. Weights and percentages of the weight relative to BW42 of gizzard, heart, lungs, liver and hematocrit were used in the QTL search. Parental, F1 and F2 individuals were genotyped with 128 genetic markers (127 microsatellites and 1 SNP) covering 22 linkage groups. QTL mapping analyses were carried out using mixed models. A total of 11 genome-wide significant QTL and five suggestive linkages were mapped. Thus, genome-wide significant QTL with similar effects across sexes were mapped to GGA2, 4 and 14 for heart weight, and to GGA2, 8 and 12 for gizzard %. Additionally, five genome-wide significant QTL with different effects across sexes were mapped to GGA 8, 19 and 26 for heart weight; GGA26 for heart % and GGA3 for hematocrit value. Five QTL were detected in chromosomal regions where QTL for similar traits were previously mapped in other F2 chicken populations. Seven novel genome-wide significant QTL are reported here, and 21 positional candidate genes in QTL regions were identified.

Variant discovery in a QTL region on chromosome 3 associated with fatness in chickens.

Abdominal fat content is an economically important trait in commercially bred chickens. Although many quantitative trait loci (QTL) related to fat deposition have been detected, the resolution for these regions is low and functional variants are still unknown. The current study was conducted aiming at increasing resolution for a region previously shown to have a QTL associated with fat deposition, to detect novel variants from this region and to annotate those variants to delineate potentially functional ones as candidates for future studies. To achieve this, 18 chickens from a parental generation used in a reciprocal cross between broiler and layer lines were sequenced using the Illumina next-generation platform with an initial coverage of 18X/chicken. The discovery of genetic variants was performed in a QTL region located on chromosome 3 between microsatellite markers LEI0161 and ADL0371 (33,595,706-42,632,651 bp). A total of 136,054 unique SNPs and 15,496 unique INDELs were detected in this region, and after quality filtering, 123,985 SNPs and 11,298 INDELs were retained. Of these variants, 386 SNPs and 15 INDELs were located in coding regions of genes related to important metabolic pathways. Loss-of-function variants were identified in several genes, and six of those, namely LOC771163, EGLN1, GNPAT, FAM120B, THBS2 and GGPS1, were related to fat deposition. Therefore, these loss-of-function variants are candidate mutations for conducting further studies on this important trait in chickens.

SNP and INDEL detection in a QTL region on chicken chromosome 2 associated with muscle deposition.

Genetic improvement is important for the poultry industry, contributing to increased efficiency of meat production and quality. Because breast muscle is the most valuable part of the chicken carcass, knowledge of polymorphisms influencing this trait can help breeding programs. Therefore, the complete genome of 18 chickens from two different experimental lines (broiler and layer) from EMBRAPA was sequenced, and SNPs and INDELs were detected in a QTL region for breast muscle deposition on chicken chromosome 2 between microsatellite markers MCW0185 and MCW0264 (105,849-112,649 kb). Initially, 94,674 unique SNPs and 10,448 unique INDELs were identified in the target region. After quality filtration, 77% of the SNPs (85,765) and 60% of the INDELs (7828) were retained. The studied region contains 66 genes, and functional annotation of the filtered variants identified 517 SNPs and three INDELs in exonic regions. Of these, 357 SNPs were classified as synonymous, 153 as non-synonymous, three as stopgain, four INDELs as frameshift and three INDELs as non-frameshift. These exonic mutations were identified in 37 of the 66 genes from the target region, three of which are related to muscle development (DTNA, RB1CC1 and MOS). Fifteen non-tolerated SNPs were detected in several genes (MEP1B, PRKDC, NSMAF, TRAPPC8, SDR16C5, CHD7, ST18 and RB1CC1). These loss-of-function and exonic variants present in genes related to muscle development can be considered candidate variants for further studies in chickens. Further association studies should be performed with these candidate mutations as should validation in commercial populations to allow a better explanation of QTL effects.

Npas4 is activated by melatonin, and drives the clock gene Cry1 in the ovine pars tuberalis.

Seasonal mammals integrate changes in the duration of nocturnal melatonin secretion to drive annual physiologic cycles. Melatonin receptors within the proximal pituitary region, the pars tuberalis (PT), are essential in regulating seasonal neuroendocrine responses. In the ovine PT, melatonin is known to influence acute changes in transcriptional dynamics coupled to the onset (dusk) and offset (dawn) of melatonin secretion, leading to a potential interval-timing mechanism capable of decoding changes in day length (photoperiod). Melatonin offset at dawn is linked to cAMP accumulation, which directly induces transcription of the clock gene Per1. The rise of melatonin at dusk induces a separate and distinct cohort, including the clock-regulated genes Cry1 and Nampt, but little is known of the up-stream mechanisms involved. Here, we used next-generation sequencing of the ovine PT transcriptome at melatonin onset and identified Npas4 as a rapidly induced basic helix-loop-helix Per-Arnt-Sim domain transcription factor. In vivo we show nuclear localization of NPAS4 protein in presumptive melatonin target cells of the PT (α-glycoprotein hormone-expressing cells), whereas in situ hybridization studies identified acute and transient expression in the PT of Npas4 in response to melatonin. In vitro, NPAS4 forms functional dimers with basic helix loop helix-PAS domain cofactors aryl hydrocarbon receptor nuclear translocator (ARNT), ARNT2, and ARNTL, transactivating both Cry1 and Nampt ovine promoter reporters. Using a combination of 5'-deletions and site-directed mutagenesis, we show NPAS4-ARNT transactivation to be codependent upon two conserved central midline elements within the Cry1 promoter. Our data thus reveal NPAS4 as a candidate immediate early-response gene in the ovine PT, driving molecular responses to melatonin.

Many quantitative trait loci for feather growth in an F(2) broiler × layer cross collocate with body weight loci.

1. A genome-wide scan of 467 F(2) progeny of a broiler x layer cross was conducted to identify quantitative trait loci (QTL) affecting the rate of growth of the tail, wing and back feathers, and the width of the breast feather tract, at three weeks of age. 2. Correlations between the traits ranged from 0·36 to 0·61. Males had longer tail and wing feathers and shorter back feathers than females. Breast feather tract width was greater in females than males. 3. QTL effects were generally additive and accounted for 11 to 45% of sex average feather lengths of the breeds, and 100% of the breast feather tract width. Positive and negative alleles were inherited from both lines, whereas the layer allele was larger than the broiler allele after adjusting for body weight. 4. A total of 4 genome-significant and 4 suggestive QTL were detected. At three or 6 weeks of age, 5 of the QTL were located in similar regions as QTL for body weight. 5. Analysis of a model with body weight at three weeks as a covariate identified 5 genome significant and 6 suggestive QTL, of which only two were coincident with body weight QTL. One QTL for feather length at 148 cM on GGA1 was identified at a similar location in the unadjusted analysis. 6. The results suggest that the rate of feather growth is largely controlled by body weight QTL, and that QTL specific for feather growth also exist.

Quantitative trait loci associated with chemical composition of the chicken carcass.

Major objectives of the poultry industry are to increase meat production and to reduce carcass fatness, mainly abdominal fat. Information on growth performance and carcass composition are important for the selection of leaner meat chickens. To enhance our understanding of the genetic architecture underlying the chemical composition of chicken carcasses, an F(2) population developed from a broiler × layer cross was used to map quantitative trait loci (QTL) affecting protein, fat, water and ash contents in chicken carcasses. Two genetic models were applied in the QTL analysis: the line-cross and the half-sib models, both using the regression interval mapping method. Six significant and five suggestive QTL were mapped in the line-cross analysis, and four significant and six suggestive QTL were mapped in the half-sib analysis. A total of eleven QTL were mapped for fat (ether extract), five for protein, four for ash and one for water contents in the carcass using both analyses. No study to date has reported QTL for carcass chemical composition in chickens. Some QTL mapped here for carcass fat content match, as expected, QTL regions previously associated with abdominal fat in the same or in different populations, and novel QTL for protein, ash and water contents in the carcass are presented here. The results described here also reinforce the need for fine mapping and to perform multi-trait analyses to better understand the genetic architecture of these traits.

Complex traits analysis of chicken growth using targeted genetical genomics.

Dissecting the genetic control of complex trait variation remains very challenging, despite many advances in technology. The aim of this study was to use a major growth quantitative trait locus (QTL) in chickens mapped to chromosome 4 as a model for a targeted approach to dissect the QTL. We applied a variant of the genetical genomics approach to investigate genome-wide gene expression differences between two contrasting genotypes of a marked QTL. This targeted approach allows the direct quantification of the link between the genotypes and the genetic responses, thus narrowing the QTL-phenotype gap using fewer samples (i.e. microarrays) compared with the genome-wide genetical genomics studies. Four differentially expressed genes were localized under the region of the QTL. One of these genes is a potential positional candidate gene (AADAT) that affects lysine and tryptophan metabolism and has alternative splicing variants between the two genotypes. In addition, the lysine and glycolysis metabolism pathways were significantly enriched for differentially expressed genes across the genome. The targeted approach provided a complementary route to fine mapping of QTL by characterizing the local and the global downstream effects of the QTL and thus generating further hypotheses about the action of that QTL.

Bone mineral density QTL at sexual maturity and end of lay.

1. An F2 cross of a broiler male line and a White Leghorn layer line was used to identify quantitative trait loci (QTL) for bone density at the onset of lay and at the end of the laying period. A total of 686 measures of humeral bone density were available for analysis. 2. There was no evidence for epistasis. 3. Genome-wide significant QTL for bone density at the onset of lay were identified on chromosomes 1 (311 cM) and 8 (2 cM) and on chromosomes 1 (311 cM), 3 (57 cM) and 8 (2 cM) with a covariate for the number of yellow follicles (a proxy for the concentration of circulating oestrogen). 4. Evidence for only 4 chromosome-wide suggestive QTL were detected at the end of lay (72 weeks). 5. Analysis of the combined data confirmed two genome-wide suggestive QTL on chromosome 1 (137 and 266 cM) and on chromosomes 8 (2 cM) and 9 (10 cM) in analyses with or without the covariate. 6. Positive QTL alleles came from the broiler line with the exception of 2 suggestive QTL at the onset of lay on chromosomes 3 and 5 in an analysis with the covariate. 7. In general, QTL acted additively, except that dominant effects were identified for three suggestive QTL at the onset of lay on chromosomes 3 (57 and 187 cM) and 5 (9 cM). 8. The significant QTL in this study were at similar locations to QTL identified in a range of crosses in other publications, suggesting that they are prime candidates for the search for genes and mutations that could be used as selection criteria to improve bone strength and decrease fractures in commercial laying hens.

QTL for percentage of carcass and carcass parts in a broiler x layer cross.

An F2 experimental population, developed from a broiler layer cross, was used in a genome scan of QTL for percentage of carcass, carcass parts, shank and head. Up to 649 F2 chickens from four paternal half-sib families were genotyped with 128 genetic markers covering 22 linkage groups. Total map length was 2630 cM, covering approximately 63% of the genome. QTL interval mapping using regression methods was applied to line-cross and half-sib models. Under the line-cross model, 12 genome-wide significant QTL and 17 suggestive linkages for percentages of carcass parts, shank and head were mapped to 13 linkage groups (GGA1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 14, 18 and 27). Under the paternal half-sib model, six genome-wide significant QTL and 18 suggestive linkages for percentages of carcass parts, shank and head were detected on nine chicken linkage groups (GGA1, 2, 3, 4, 5, 12, 14, 15 and 27), seven of which seemed to corroborate positions revealed by the previous model. Overall, three novel QTL of importance to the broiler industry were mapped (one significant for shank% on GGA3 and two suggestive for carcass and breast percentages on GGA14 and drums and thighs percentage on GGA15). One novel QTL for wings% was mapped to GGA3, six novel QTL (GGA1, 3, 7, 8, 9 and 27) and suggestive linkages (GGA2, 4, and 5) were mapped for head%, and suggestive linkages were identified for back% on GGA2, 11 and 12. In addition, many of the QTL mapped in this study confirmed QTL previously reported in other populations.

Overlap of quantitative trait loci for early growth rate, and for body weight and age at onset of sexual maturity in chickens.

Critical age, weight and body composition have been suggested as necessary correlates of sexual maturity. A genome scan to identify quantitative trait loci (QTL) for age and body weight at first egg (AFE and WFE) was conducted on 912 birds from an F(2) broiler-layer cross using 106 microsatellite markers. Without a covariate, QTL for body WFE were detected on chromosomes 2, 4, 8, 27 and Z and a single QTL for AFE was detected on chromosome 2. With AFE as a covariate, additional QTL for body WFE were found on chromosomes 1 and 13, with abdominal fat pad as covariate a QTL for body WFE was found on chromosome 1. With body WFE as covariate, additional QTL for AFE were found on chromosomes 1, 3, 4, 13 and 27. The QTL generally acted additively and there was no evidence for epistasis. Consistent with the original line differences, broiler alleles had positive effects on body WFE and negative effects on AFE, whereas the phenotypic correlation between the two traits was positive. The mapped QTL for body WFE cumulatively accounted for almost half the body weight difference between the chicken lines at puberty. Overlapping QTL for body WFE and body weight to 9 weeks of age indicate that most QTL affecting growth rate also affect body WFE. The co-localisation of QTL for body weight, growth and sexual maturity suggests that body weight and growth rate are closely related to the attainment of sexual maturity and that the genetic determination of growth rate has correlated effects on puberty.

Identification of chromosomal regions associated with growth and carcass traits in an F(3) full sib intercross line originating from a cross of chicken lines divergently selected on body weight.

An F(3) resource population originating from a cross between two divergently selected lines for high (D+ line) or low (D- line) body weight at 8-weeks of age (BW55) was generated and used for Quantitative Trait Locus (QTL) mapping. From an initial cross of two founder F(0) animals from D(+) and D(-) lines, progeny were randomly intercrossed over two generations following a full sib intercross line (FSIL) design. One hundred and seventy-five genome-wide polymorphic markers were employed in the DNA pooling and selective genotyping of F(3) to identify markers with significant effects on BW55. Fifty-three markers on GGA2, 5 and 11 were then genotyped in the whole F(3) population of 503 birds, where interval mapping with GridQTL software was employed. Eighteen QTL for body weight, carcass traits and some internal organ weights were identified. On GGA2, a comparison between 2-QTL vs. 1-QTL analysis revealed two separate QTL regions for body, feet, breast muscle and carcass weight. Given co-localization of QTL for some highly correlated traits, we concluded that there were 11 distinct QTL mapped. Four QTL localized to already mapped QTL from other studies, but seven QTL have not been previously reported and are hence novel and unique to our selection line. This study provides a low resolution QTL map for various traits and establishes a genetic resource for future fine-mapping and positional cloning in the advanced FSIL generations.

Quantitative trait loci associated with fatness in a broiler-layer cross.

An F(2) population established by crossing a broiler male line and a layer line was used to map quantitative trait loci (QTL) affecting abdominal fat weight, abdominal fat percentage and serum cholesterol and triglyceride concentrations. Two genetic models, the line-cross and the half-sib, were applied in the QTL analysis, both using the regression interval method. Three significant QTL and four suggestive QTL were mapped in the line-cross analysis and four significant and four suggestive QTL were mapped in the half-sib analysis. A total of five QTL were mapped for abdominal fat weight, six for abdominal fat percentage and four for triglyceride concentration in both analyses. New QTL associated with serum triglyceride concentration were mapped on GGA5, GGA23 and GG27. QTL mapped between markers LEI0029 and ADL0371 on GGA3 for abdominal fat percentage and abdominal fat weight and a suggestive QTL on GGA12 for abdominal fat percentage showed significant parent-of-origin effects. Some QTL mapped here match QTL regions mapped in previous studies using different populations, suggesting good candidate regions for fine-mapping and candidate gene searches.

Quantitative trait loci for performance traits in a broiler x layer cross.

An F(2) resource population, derived from a broiler x layer cross, was used to map quantitative trait loci (QTL) for body weights at days 1, 35 and 41, weight gain, feed intake, feed efficiency from 35 to 41 days and intestinal length. Up to 577 F(2) chickens were genotyped with 103 genetic markers covering 21 linkage groups. A preliminary QTL mapping report using this same population focused exclusively on GGA1. Regression methods were applied to line-cross and half-sib models for QTL interval mapping. Under the line-cross model, eight QTL were detected for body weight at 35 days (GGA2, 3 and 4), body weight at 41 days (GGA2, 3, 4 and 10) and intestine length (GGA4). Under the half-sib model, using sire as common parent, five QTL were detected for body weight at day 1 (GGA3 and 18), body weight at 35 days (GGA2 and 3) and body weight at 41 days (GGA3). When dam was used as common parent, seven QTL were mapped for body weight at day 1 (GGA2), body weight at day 35 (GGA2, 3 and 4) and body weight at day 41 (GGA2, 3 and 4). Growth differences in chicken lines appear to be controlled by a chronological change in a limited number of chromosomal regions.

Avian genomics in the 21st century.

The chicken has long been an important model organism for developmental biology, as well as a major source of protein with billions of birds used in meat and egg production each year. Chicken genomics has been transformed in recent years, with the characterisation of large EST collections and most recently with the assembly of the chicken genome sequence. As the first livestock genome to be fully sequenced it leads the way for others to follow--with zebra finch later this year. The genome sequence and the availability of three million genetic polymorphisms are expected to aid the identification of genes that control traits of importance in poultry. As the first bird genome to be sequenced it is a model for the remaining 9,600 species thought to exist today. Many of the features of avian biology and organisation of the chicken genome make it an ideal model organism for phylogenetics and embryology, along with applications in agriculture and medicine. The availability of new tools such as whole-genome gene expression arrays and SNP panels, coupled with information resources on the genes and proteins are likely to enhance this position.

Quantitative trait loci for bone traits segregating independently of those for growth in an F2 broiler x layer cross.

An F2 broiler-layer cross was phenotyped for 18 skeletal traits at 6, 7 and 9 weeks of age and genotyped with 120 microsatellite markers. Interval mapping identified 61 suggestive and significant QTL on 16 of the 25 linkage groups for 16 traits. Thirty-six additional QTL were identified when the assumption that QTL were fixed in the grandparent lines was relaxed. QTL with large effects on the lengths of the tarsometatarsus, tibia and femur, and the weights of the tibia and femur were identified on GGA4 between 217 and 249 cM. Six QTL for skeletal traits were identified that did not co-locate with genome wide significant QTL for body weight and two body weight QTL did not coincide with skeletal trait QTL. Significant evidence of imprinting was found in ten of the QTL and QTL x sex interactions were identified for 22 traits. Six alleles from the broiler line for weight- and size-related skeletal QTL were positive. Negative alleles for bone quality traits such as tibial dyschondroplasia, leg bowing and tibia twisting generally originated from the layer line suggesting that the allele inherited from the broiler is more protective than the allele originating from the layer.

Emergence of the chicken as a model organism: implications for agriculture and biology.

Many of the features of the chicken make it an ideal model organism for phylogenetics and embryology, along with applications in agriculture and medicine. The availability of new tools such as whole genome gene expression arrays and single nucleotide polymorphism panels, coupled with the genome sequence, will enhance this position. These advances are reviewed and their implications are discussed.