Identification of Trait Loci Affecting White Meat Percentage and Other Growth and Carcass Traits in Commercial Broiler Chickens

Artificial selection footprints in indigenous and commercial chicken genomes

BACKGROUND

Although many studies have been done to reveal artificial selection signatures in commercial and indigenous chickens, a limited number of genes have been linked to specific traits. To identify more trait-related artificial selection signatures and genes, we re-sequenced a total of 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan Province, China.

RESULTS

We found 30 million non-redundant single nucleotide variants and small indels (< 50 bp) in the indigenous chickens, of which 10 million were not seen in 60 broilers, 56 layers and 35 red jungle fowls (RJFs) that we compared with. The variants in each breed are enriched in non-coding regions, while those in coding regions are largely tolerant, suggesting that most variants might affect cis-regulatory sequences. Based on 27 million bi-allelic single nucleotide polymorphisms identified in the chickens, we found numerous selective sweeps and affected genes in each indigenous chicken breed and substantially larger numbers of selective sweeps and affected genes in the broilers and layers than previously reported using a rigorous statistical model. Consistent with the locations of the variants, the vast majority (~ 98.3%) of the identified selective sweeps overlap known quantitative trait loci (QTLs). Meanwhile, 74.2% known QTLs overlap our identified selective sweeps. We confirmed most of previously identified trait-related genes and identified many novel ones, some of which might be related to body size and high egg production traits. Using RT-qPCR, we validated differential expression of eight genes (GHR, GHRHR, IGF2BP1, OVALX, ELF2, MGARP, NOCT, SLC25A15) that might be related to body size and high egg production traits in relevant tissues of relevant breeds.

CONCLUSION

We identify 30 million single nucleotide variants and small indels in the five indigenous chicken breeds, 10 million of which are novel. We predict substantially more selective sweeps and affected genes than previously reported in both indigenous and commercial breeds. These variants and affected genes are good candidates for further experimental investigations of genotype-phenotype relationships and practical applications in chicken breeding programs.

Expression profile and the G63A mutation of IGF2 gene associated with growth traits in Zhedong-White goose

Insulin-like growth factors 2 (IGF2) is an insulin-like growth factor that plays a major role in animal growth, cell proliferation and differentiation, as well as reproduction. IGF2 is well-known to be a candidate gene of growth and reproductive traits in many agricultural animals. Our previous study revealed that the G63A (Chr2: G26541617A) mutation within IGF2 exon 1 showed a significant association with egg numbers (E180d) of Sanhua goose population (p < 0.05). However, little work focus on the correlation between the IGF2 mutations and goose growth traits. In this study, qPCR indicated that the IGF2 mRNA highly expressed in leg muscle, liver, ovary and pituitary gland. Meanwhile, association analysis showed that the G63A mutation was significantly associated with the body weight of first-hatched Zhedong-White geese (BW0, p < 0.05), and strongly significantly associated with the BW2, BW4, BW6, BW8 and BW10 (p < 0.01). The GG homozygous had the lowest BW (from 4 weeks to 10 weeks) than those of AA and AG genotypes (p < 0.01), and the allele A was also positively correlated with the BW of the Zhedong-White goose population. Therefore, the G63A mutation in IGF2 may be an important genetic marker for goose breeding.

Insulin-like growth factor 2 (IGF2) gene: molecular characterization, expression analysis and association of polymorphisms with egg production traits in goose (Anser cygnoides)

Insulin-like growth factor 2 (IGF2) belongs to the member of the insulin-like growth factors family, which plays key roles in animal growth, differentiation and proliferation, as well as reproduction and the regulation of ovarian follicle development. However, little is known about the goose IGF2 gene. In this study, a 1879 bp fragment that covered the complete coding region (CDS) of goose IGF2 cDNA was identified for the first time. The cDNA consists of an open reading frame of 574 nucleotides with the capacity to encode a prepro-IGF-II protein of 187 amino acids, which comprises a signal peptide (24 residues), IGF-II peptide (67 residues), and C-terminal peptide (96 residues), and is closely related to that of chicken. qPCR indicates that the goose IGF2 mRNA is differentially expressed in all examined tissues of fertilized eggs (28 days) and laying Zhedong White geese (270 days). Two novel single nucleotide polymorphisms (SNPs) were detected in exon 1 (G63A, Chr2: G26541617A) and intron 1 (G38A, Chr2: G26541479A) regions, and the synonymous mutation G63A showed a significant association with egg numbers (E180d) of Sanhua goose population (p < 0.05). All the information derived from this study could be valuable and facilitate further studies on the functions of goose IGF2 gene.

Genome-Wide Association Study of Growth Performance and Immune Response to Newcastle Disease Virus of Indigenous Chicken in Rwanda

A chicken genome has several regions with quantitative trait loci (QTLs). However, replication and confirmation of QTL effects are required particularly in African chicken populations. This study identified single nucleotide polymorphisms (SNPs) and putative genes responsible for body weight (BW) and antibody response (AbR) to Newcastle disease (ND) in Rwanda indigenous chicken (IC) using genome-wide association studies (GWAS). Multiple testing was corrected using chromosomal false detection rates of 5 and 10% for significant and suggestive thresholds, respectively. BioMart data mining and variant effect predictor tools were used to annotate SNPs and candidate genes, respectively. A total of four significant SNPs (rs74098018, rs13792572, rs314702374, and rs14123335) significantly (p ≤ 7.6E-5) associated with BW were identified on chromosomes (CHRs) 8, 11, and 19. In the vicinity of these SNPs, four genes such as pre-B-cell leukaemia homeobox 1 (PBX1), GPATCH1, MPHOSPH6, and MRM1 were identified. Four other significant SNPs (rs314787954, rs13623466, rs13910430, and rs737507850) all located on chromosome 1 were strongly (p ≤ 7.6E-5) associated with chicken antibody response to ND. The closest genes to these four SNPs were cell division cycle 16 (CDC16), zinc finger, BED-type containing 1 (ZBED1), myxovirus (influenza virus) resistance 1 (MX1), and growth factor receptor bound protein 2 (GRB2) related adaptor protein 2 (GRAP2). Besides, other SNPs and genes suggestively (p ≤ 1.5E-5) associated with BW and antibody response to ND were reported. This work offers a useful entry point for the discovery of causative genes accountable for essential QTLs regulating BW and antibody response to ND traits. Results provide auspicious genes and SNP-based markers that can be used in the improvement of growth performance and ND resistance in IC populations based on gene-based and/or marker-assisted breeding selection.

Genome-wide association study for plasma very low-density lipoprotein concentration in chicken

The plasma very low-density lipoprotein (VLDL) concentration is an effective blood biochemical indicator that could be used to select lean chicken lines. In the current study, we used Genome-wide association study (GWAS) method to detect SNPs with significant effects on plasma VLDL concentration. As a result, 38 SNPs significantly associated with plasma VLDL concentration were identified using at least one of the three mixed linear model (MLM) packages, including GRAMMAR, EMMAX and GEMMA. Nearly, all these SNPs with significant effects on plasma VLDL concentration (except Gga_rs16160897) have significantly different allele frequencies between lean and fat lines. The 1-Mb regions surrounding these 38 SNPs were extracted, and twelve important regions were obtained after combining the overlaps. A total of 122 genes in these twelve important regions were detected. Among these genes, LRRK2, ABCD2, TLR4, E2F1, SUGP1, NCAN, KLF2 and RAB8A were identified as important genes for plasma VLDL concentration based on their basic functions. The results of this study may supply useful information to select lean chicken lines.

Mapping of Quantitative Trait Loci for Growth and Carcass-Related Traits in Chickens Using a Restriction-Site Associated DNA Sequencing Method

In the present study, quantitative trait loci (QTLs) analysis was performed to identify the chromosomal positions of growth and carcass-related trait QTLs using 319 F₂ chickens obtained from intercrosses of an Oh-Shamo male and four White Plymouth Rock females. Body weight was measured weekly until the birds were 7 weeks old. Carcass-related traits were also measured at this timepoint. A genetic linkage map was constructed using 545 single nucleotide polymorphism (SNP) markers that were developed using a restriction-site associated DNA sequencing method. The linkage map included the 23 autosomes and the Z chromosome. Using simple interval QTL mapping, we were able to identify 10 significant and suggestive main-effect QTLs for growth and carcass-related traits present on chromosomes 1, 2, 3, 5, 8, 19, 24, and Z. These loci explained 5.60–16.52% of the phenotypic variances. The chromosomal positions of the 10 QTLs overlapped with those of previously reported QTLs, whereas the targeted traits varied. Our QTLs will aid future breeding programs in improving growth and meat yield of chickens (e.g., via marker-assisted selection), particularly in the Japanese brand chicken industry.

Association of polymorphisms in Pit-1 gene with growth and feed efficiency in meat-type chickens

OBJECTIVE

The pituitary specific transcription factor-1 (Pit-1) gene is responsible for pituitary development and growth hormone expression and is regarded as a pivotal candidate gene for growth and production in chickens. Therefore, the aim of this study was to investigate the association of Pit-1 polymorphisms with growth and feed efficiency traits in yellow meat-type chickens.

METHODS

In the present study, five single nucleotide polymorphisms (SNPs) of Pit-1 were selected and genotyped by high-throughput matrix-assisted laser desorption-ionization time-of-flight mass spectrometry in 724 meat-type chickens.

RESULTS

Association analysis showed that rs13687126 of Pit-1 was strongly associated with body weight gain (BWG) and feed intake (FI) (p<0.05), and that rs13687128 was significantly correlated with body weight at 70 days of age (BW70), BWG and feed conversion ratio (FCR) (p<0.05). SNP rs13905622 was strongly related to BW70 and FCR (p<0.05). Furthermore, birds with the GG genotype of rs13687126 had larger BWG and FI than those with the AG genotype (p<0.05). Individuals with the TT genotype of rs13687128 were significantly higher BW70 and BWG than those of the CT and CC genotype, while FCR was just the opposite (p<0.05). For rs13905622, the AA chickens showed strongly larger BW70 and lower FCR compared with the AT and TT chickens (p<0.05). Additionally, an ACA haplotype based on rs13687126, rs13687128, and rs13905622 had significant effects on BW70 and FCR (p<0.05).

CONCLUSION

Our studies thus provide crucial evidence for the relationship between polymorphisms of Pit-1 and growth and feed efficiency traits which may be useful for meat-type chicken breeding programs.

Genomic Insights Into the Multiple Factors Controlling Abdominal Fat Deposition in a Chicken Model

Genetic selection for an increased growth rate in meat-type chickens has been accompanied by excessive fat accumulation particularly in abdominal cavity. These progressed to indirect and often unhealthy effects on meat quality properties and increased feed cost. Advances in genomics technology over recent years have led to the surprising discoveries that the genome is more complex than previously thought. Studies have identified multiple-genetic factors associated with abdominal fat deposition. Meanwhile, the obesity epidemic has focused attention on adipose tissue and the development of adipocytes. The aim of this review is to summarize the current understanding of genetic/epigenetic factors associated with abdominal fat deposition, or as it relates to the proliferation and differentiation of preadipocytes in chicken. The results discussed here have been identified by different genomic approaches, such as QTL-based studies, the candidate gene approach, epistatic interaction, copy number variation, single-nucleotide polymorphism screening, selection signature analysis, genome-wide association studies, RNA sequencing, and bisulfite sequencing. The studies mentioned in this review have described multiple-genetic factors involved in an abdominal fat deposition. Therefore, it is inevitable to further study the multiple-genetic factors in-depth to develop novel molecular markers or potential targets, which will provide promising applications for reducing abdominal fat deposition in meat-type chicken.

Identification of quantitative trait loci for body temperature, body weight, breast yield, and digestibility in an advanced intercross line of chickens under heat stress

Background

Losses in poultry production due to heat stress have considerable negative economic consequences. Previous studies in poultry have elucidated a genetic influence on response to heat. Using a unique chicken genetic resource, we identified genomic regions associated with body temperature (BT), body weight (BW), breast yield, and digestibility measured during heat stress. Identifying genes associated with a favorable response during high ambient temperature can facilitate genetic selection of heat-resilient chickens.

Methods

Generations F18 and F19 of a broiler (heat-susceptible) × Fayoumi (heat-resistant) advanced intercross line (AIL) were used to fine-map quantitative trait loci (QTL). Six hundred and thirty-one birds were exposed to daily heat cycles from 22 to 28 days of age, and phenotypes were measured before heat treatment, on the 1st day and after 1 week of heat treatment. BT was measured at these three phases and BW at pre-heat treatment and after 1 week of heat treatment. Breast muscle yield was calculated as the percentage of BW at day 28. Ileal feed digestibility was assayed from digesta collected from the ileum at day 28. Four hundred and sixty-eight AIL were genotyped using the 600 K Affymetrix chicken SNP (single nucleotide polymorphism) array. Trait heritabilities were estimated using an animal model. A genome-wide association study (GWAS) for these traits and changes in BT and BW was conducted using Bayesian analyses. Candidate genes were identified within 200-kb regions around SNPs with significant association signals.

Results

Heritabilities were low to moderate (0.03 to 0.35). We identified QTL for BT on Gallus gallus chromosome (GGA)14, 15, 26, and 27; BW on GGA1 to 8, 10, 14, and 21; dry matter digestibility on GGA19, 20 and 21; and QTL of very large effect for breast muscle yield on GGA1, 15, and 22 with a single 1-Mb window on GGA1 explaining more than 15 % of the genetic variation.

Conclusions

This is the first study to estimate heritabilities and perform GWAS using this AIL for traits measured during heat stress. Significant QTL as well as low to moderate heritabilities were found for each trait, and these QTL may facilitate selection for improved animal performance in hot climatic conditions.

Re-sequencing data for refining candidate genes and polymorphisms in QTL regions affecting adiposity in chicken

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.

Genetic analysis of an F2 intercross between two strains of Japanese quail provided evidence for quantitative trait loci affecting carcass composition and internal organs

The purpose of this study was to identify genomic regions, quantitative trait loci (QTL), affecting carcass traits on chromosome 1 in an F2 population of Japanese quail. For this purpose, two white and wild strains of Japanese quail (16 birds) were crossed reciprocally and F1 generation (34 birds) was created. The F2 generation was produced by intercrossing of the F1 birds. Phenotypic data including carcass weight, internal organs and carcass parts were collected on F2 animals (422 birds). The total mapping population (472 birds) was genotyped for 8 microsatellite markers on chromosome 1. QTL analysis was performed with interval mapping method applying the line-cross model. Significant QTL were identified for breast weight at 0 (P < 0.01), 172 (P < 0.05) and 206 (P < 0.01), carcass weight at 91 (P < 0.05), carcass fatness at 0 (P < 0.01), pre-stomach weight at 206 (P < 0.01) and uropygial weight gland at 197 (P < 0.01) cM on chromosome 1. There was also evidence for imprinted QTL affecting breast weight (P < 0.01) on chromosome 1. The proportion of the F2 phenotypic variation explained by the significant additive, dominance and imprinted QTL effects ranged from 1.0 to 7.3%, 1.2 to 3.3% and 1.4 to 2.2%, respectively.

Identification of QTL for live weight and growth rate using DNA markers on chromosome 3 in an F2 population of Japanese quail

The Japanese quail (Coturnix japonica) is an important agricultural species and is an animal model for genetic researches. This study was conducted to identify quantitative trait loci (QTL) affecting live weight and growth rate on chromosome 3 in quail. Two strains of Japanese quail including wild and white were crossed reciprocally and F1 generation was created. The birds from F2 generation were measured for growth traits and all of 472 birds (8 pairs from the parental strains, 34 F1 birds and 422 F2 birds) were genotyped for microsatellite markers on chromosome 3. The results indicated chromosome wide significant QTL for hatching weight (P < 0.01) and weight at 1, 2, 3 and 4 weeks of age, average daily gain from hatch to 1, 1-2 and 3-4 weeks of age and Kleiber ratio (P < 0.05), an indirect criterion of feed efficiency. The highest QTL additive and imprinting effects (2.72 and 0.79 % of the trait variation in the F2 population, respectively) were related to hatching weight. The identified QTL for this trait (at 7 cM relative to the centromeric region of the chromosome) had significant interaction with sex and hatch (P < 0.01). The dominance effect of QTL was significant (P < 0.05) for bodyweight at one week of age accounting for 1.69 % of the trait variation in the F2 population.

A genome-wide scan of selective sweeps in two broiler chicken lines divergently selected for abdominal fat content

Background

Genomic regions controlling abdominal fatness (AF) were studied in the Northeast Agricultural University broiler line divergently selected for AF. In this study, the chicken 60KSNP chip and extended haplotype homozygosity (EHH) test were used to detect genome-wide signatures of AF.

Results

A total of 5357 and 5593 core regions were detected in the lean and fat lines, and 51 and 57 reached a significant level (P<0.01), respectively. A number of genes in the significant core regions, including RB1, BBS7, MAOA, MAOB, EHBP1, LRP2BP, LRP1B, MYO7A, MYO9A and PRPSAP1, were detected. These genes may be important for AF deposition in chickens.

Conclusions

We provide a genome-wide map of selection signatures in the chicken genome, and make a contribution to the better understanding the mechanisms of selection for AF content in chickens. The selection for low AF in commercial breeding using this information will accelerate the breeding progress.

Whole-genome scan for signatures of recent selection reveals loci associated with important traits in White Leghorn chickens

Chicken is considered to be an excellent model for genetic studies of phenotypic and genomic evolution, with large effective population size, specialized commercial lines, and strong human-driven selection. High-density chicken SNP chips can help to achieve a better understanding of the selection mechanisms in artificially selected populations. We performed the genome-wide tests for the selection signature in 385 White Leghorn hens and mapped positively selected regions to the genome annotations. Ten QTL related to egg production, egg quality, growth, and disease resistance traits were selected for extended haplotype homozygosity tests to give a brief overview of recent selection signatures in chicken QTL. We also reported 185 candidate genes/CDSs showing top P-values and slower decay of haplotype homozygosities. Some of these genes seemed to have significant effects on important economical traits, and most of them have not been reported in chickens. The current study provides a genome-wide map of linkage disequilibrium extents and distributions and selection footprints in the chicken genome. A panel of genes, including PRL, NCKX1, NRF1, LHX2, and SFRP1 associated with egg production, metabolism traits, and response to illumination were identified. In addition, there were more genes identified that have not yet been reported in chickens, and our results provide new clues for further study.

Polymorphisms of Pit-1 gene and its association with growth traits in chicken

The Pit-1 gene is involved in regulation of muscle growth through controlling the expression of growth hormone, prolactin, and transforming growth factor-β genes in chicken. The objectives of the study were to explore polymorphisms of the Pit-1 gene and to estimate the effect of these polymorphisms on growth traits in PB-1 and control (broiler strain) and IWI (layer strain) chickens. Single-stranded conformation polymorphism followed by sequencing was performed to reveal polymorphisms of the gene. In total, 10 haplotypes were found across the lines. The mRNA expression of Pit-1 varied among haplogroups and had a significant effect on BW and growth rates. The haplogroups showed a significant effect on BW in wk 7 in PB-1 chickens. In control chickens there was a significant effect at d 1 and in wk 2 and 7, and in IWI strains, there was a significant effect at d 1 and wk 6 and 7. The significant association of haplogroups and growth rate was found between 0 and 2 wk in control and between 0 and 2 and 6 and 7 wk in IWI strains. It was concluded that the Pit-1 gene is polymorphic and has a significant effect on growth traits in chickens.

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: III. Fat deposition and intramuscular fat content

In this study, a genome scan was performed to detect genomic loci that affect fat deposition in white adipose tissues and muscles in 278 F (2) males of reciprocal crosses between the genetically and phenotypically extreme inbred chicken lines New Hampshire (NHI) and White Leghorn (WL77). Genome-wide highly significant quantitative trait loci (QTL) influencing fat deposition in white adipose tissues were found on GGA2 and 4. The peak QTL positions for different visceral and subcutaneous white adipose tissues were located between 41.4 and 112.4 Mb on GGA2 and between 76.2 and 78.7 Mb on GGA4, which explained 4.2-10.4% and 4.3-11.6% respectively of the phenotypic F (2) variances. Contrary to our expectations, the QTL allele descending from the lean line WL77 on GGA4 led to increased fat deposition. We suggest a transgressive action of the obesity allele only if it is not in the genetic background of the line WL77. Additional highly significant loci for subcutaneous adipose tissue mass were identified on GGA12 and 15. For intramuscular fat content, a suggestive QTL was located on GGA14. The analysed crosses provide a valuable resource for further fine mapping of fatness genes and subsequent gene discovery.

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.

Genome Scan for Parent-of-Origin QTL Effects on Bovine Growth and Carcass Traits

Parent-of-origin effects (POE) such as genomic imprinting influence growth and body composition in livestock, rodents, and humans. Here, we report the results of a genome scan to detect quantitative trait loci (QTL) with POE on growth and carcass traits in Angus × Brahman cattle crossbreds. We identified 24 POE–QTL on 15 Bos taurus autosomes (BTAs) of which six were significant at 5% genome-wide (GW) level and 18 at the 5% chromosome-wide (CW) significance level. Six QTL were paternally expressed while 15 were maternally expressed. Three QTL influencing post-weaning growth map to the proximal end of BTA2 (linkage region of 0–9 cM; genomic region of 5.0–10.8 Mb), for which only one imprinted ortholog is known so far in the human and mouse genomes, and therefore may potentially represent a novel imprinted region. The detected QTL individually explained 1.4 ∼ 5.1% of each trait’s phenotypic variance. Comparative in silico analysis of bovine genomic locations show that 32 out of 1,442 known mammalian imprinted genes from human and mouse homologs map to the identified QTL regions. Although several of the 32 genes have been associated with quantitative traits in cattle, only two (GNAS and PEG3) have experimental proof of being imprinted in cattle. These results lend additional support to recent reports that POE on quantitative traits in mammals may be more common than previously thought, and strengthen the need to identify and experimentally validate cattle orthologs of imprinted genes so as to investigate their effects on quantitative traits.

A proximal genomic region of mouse chromosome 10 contains quantitative trait loci affecting fatness

Body weight and fatness are quantitative traits of agricultural and medical importance. In previous genome-wide quantitative trait locus (QTL) analyses, two QTLs for body weight and weight gain at an early postnatal growth period were discovered on mouse chromosome 10 from a gene pool of wild subspecies mice, Mus musculus castaneus. In this study, we developed a congenic strain with an approximately 63-Mb wild-derived genomic region on which the two growth QTLs could be located, by recurrent backcrossing to the common inbred strain C57BL/6J. We compared body weights at 1-10 weeks of age, body weight gains at 1-3, 3-6 and 6-10 weeks, internal organ weights and body lengths between the congenic strain developed and C57BL/6J. Unfortunately, no effects of the two growth QTLs on body weights and weight gains were confirmed. However, at least two new QTLs affecting fatness traits were discovered within the introgressed congenic region. The wild-derived allele at one QTL increased body mass index, whereas at another one it decreased white fat pad weight and adiposity index. Thus, the congenic mouse strain developed here is a useful model animal for understanding the genetic and molecular basis of fat deposition in livestock as well as humans.

Evaluation of the IGFs (IGF1 and IGF2) genes as candidates for growth, body measurement, carcass, and reproduction traits in Beijing You and Silkie chickens

Insulin-like growth factors are crucial in cellular growth, differentiation, and reproduction by mediating many of the actions of growth hormone in chickens. To determine whether insulin-like growth factors genes (IGFs) are associated with important economic traits in chicken or not, we herein analyzed the association between two single nucleotide polymorphisms (SNPs) within IGF1 and IGF2 and twenty-seven growth, body measurement, carcass, and reproduction traits in two Chinese native breeds, i.e., Beijing You and Silkies. With marker-trait association analysis, we found that SNP IGF1-PstI, within the 5' flanking region of IGF1, was significantly associated with body weight at 8 (BW8), 10 (BW10), and 13 (BW13) wk of age; and shank length (SL13) and shank circumference (SC13) at 13 wk of age in Silkie population (P < 0.05). The SNP IGF2-MspI within the exon2 of IGF2 showed a significant association with body weight (BW17) and carcass weight (CW17) at 17 wk of age in Beijing You population (P < 0.05). Our findings implied that the SNPs within IGF1 and IGF2 genes could be in linkage disequilibrium with the actual causative mutations that affect growth and carcass traits.

Mapping main, epistatic and sex-specific QTL for body composition in a chicken population divergently selected for low or high growth rate

Background

Delineating the genetic basis of body composition is important to agriculture and medicine. In addition, the incorporation of gene-gene interactions in the statistical model provides further insight into the genetic factors that underlie body composition traits. We used Bayesian model selection to comprehensively map main, epistatic and sex-specific QTL in an F₂ reciprocal intercross between two chicken lines divergently selected for high or low growth rate.

Results

We identified 17 QTL with main effects across 13 chromosomes and several sex-specific and sex-antagonistic QTL for breast meat yield, thigh + drumstick yield and abdominal fatness. Different sets of QTL were found for both breast muscles [Pectoralis (P) major and P. minor], which suggests that they could be controlled by different regulatory mechanisms. Significant interactions of QTL by sex allowed detection of sex-specific and sex-antagonistic QTL for body composition and abdominal fat. We found several female-specific P. major QTL and sex-antagonistic P. minor and abdominal fatness QTL. Also, several QTL on different chromosomes interact with each other to affect body composition and abdominal fatness.

Conclusions

The detection of main effects, epistasis and sex-dimorphic QTL suggest complex genetic regulation of somatic growth. An understanding of such regulatory mechanisms is key to mapping specific genes that underlie QTL controlling somatic growth in an avian model.

Microsatellite variability and its relationship with growth, egg production, and immunocompetence traits in chickens

Variability of microsatellites and a possible relationship with growth, egg production, and immunocompetence traits were estimated for six crossbred chicken populations of White Leghorn. Nine microsatellite markers were explored; an association study used the least square maximum-likelihood method on 170 birds of six genetic groups. Seven microsatellites were polymorphic, with two to four alleles. The polymorphism information content (PIC) of five markers was more than 52%. Microsatellites MCW0041, ADL0210, and MCW0110 were significantly (P < 0.05) associated with egg production traits. Genotype 33 of MCW0041 had the highest egg production, up to 64 and 72 weeks of age. Genotypes 11 and 13 of this marker produced the lowest number of eggs. The heterozygous genotype 34 of ADL0210 had the highest egg production, up to 52, 64, and 72 weeks of age. Homozygote 11 of MCW0110 produced the highest number of eggs, up to 28 weeks of age. MCW0041 was significantly (P < 0.05) associated with body weight at 28 and 40 weeks of age. No microsatellite was significantly associated with egg weight at any age, with age at sexual maturity, or with immune response to sheep RBC.

Polymorphisms of three neuroendocrine-correlated genes associated with growth and reproductive traits in the chicken

The identification and utilization of potential candidate genes for QTL with significant effects on economically important traits are becoming increasingly important in poultry breeding programs. Chicken insulin-like growth factor binding protein 1 and 3 and signal transducers and activators of transcription 5B (STAT5B) genes are 3 essential nodes for signaling pathways and gene networks of growth and reproduction. The pooled DNA sequencing approach was used for identification of 9 SNP of the 5' upstream region of the 3 genes. A total of 826 individuals from Beijing You chicken were genotyped for 5 SNP using a modified PCR-RFLP method and the association with chicken growth and reproductive traits was studied using the GLM procedure. The T56039403C (T-808C) SNP of the insulin-like growth factor binding protein 1 gene was associated with BW at 10 wk of age (P = 0.0061), and the C56072547T (C-968T) SNP of the insulin-like growth factor binding protein 3 gene was associated with BW at 8 and 10 wk of age (P = 0.0056 and P = 0.0016, respectively). The C4535156T (C-1591T), G4533815A (G-250A), and G4533675C (G-110C) SNP of the STAT5B gene were associated with age at first egg (P = 0.0143, P = 0.0088, and P = 0.0114, respectively). Moreover, Lewontin's D' (|D'|) and r(2) of C4535156T and G4533815A SNP, C4535156T and G4533675C SNP, and G4533815A and G4533675C SNP of the STAT5B gene were 0.939 and 0.852, 0.967 and 0.858, and 0.971 and 0.896, respectively. The 3 SNP were strong-linked with each other and lay within a haplotype block. Our results suggest that these SNP were significantly associated with early growth or with sexual maturation in chickens, or both, and may be potential molecular markers for MAS.

Genetic mapping of quantitative trait loci affecting growth and carcass traits in F2 intercross chickens

We constructed a chicken F(2) resource population to facilitate the genetic improvement of economically important traits, particularly growth and carcass traits. An F(2) population comprising 240 chickens obtained by crossing a Shamo (lean, lightweight Japanese native breed) male and White Plymouth Rock breed (fat, heavyweight broiler) females was measured for BW, carcass weight (CW), abdominal fat weight (AFW), breast muscle weight (BMW), and thigh muscle weight (TMW) and was used for genome-wide linkage and QTL analysis, using a total of 240 microsatellite markers. A total of 14 QTL were detected at a 5% chromosome-wide level, and 7 QTL were significant at a 5% experiment-wide level for the traits evaluated in the F(2) population. For growth traits, significant and suggestive QTL affecting BW (measured at 6 and 9 wk) and average daily gain were identified on similar regions of chromosomes 1 and 3. For carcass traits, the QTL effects on CW were detected on chromosomes 1 and 3, with the greatest F-ratio of 15.0 being obtained for CW on chromosome 3. Quantitative trait loci positions affecting BMW and TMW were not detected at the same loci as those detected for BMW percentage of CW and TMW percentage of CW. For AFW, QTL positions were detected at the same loci as those detected for AFW percentage of CW. The present study identified significant QTL affecting BW, CW, and AFW.

A comprehensive analysis of QTL for abdominal fat and breast muscle weights on chicken chromosome 5 using a multivariate approach

Quantitative trait loci (QTL) influencing the weight of abdominal fat (AF) and of breast muscle (BM) were detected on chicken chromosome 5 (GGA5) using two successive F(2) crosses between two divergently selected 'Fat' and 'Lean' INRA broiler lines. Based on these results, the aim of the present study was to identify the number, location and effects of these putative QTL by performing multitrait and multi-QTL analyses of the whole available data set. Data concerned 1186 F(2) offspring produced by 10 F(1) sires and 85 F(1) dams. AF and BM traits were measured on F(2) animals at slaughter, at 8 (first cross) or 9 (second cross) weeks of age. The F(0), F(1) and F(2) birds were genotyped for 11 microsatellite markers evenly spaced along GGA5. Before QTL detection, phenotypes were adjusted for the fixed effects of sex, F(2) design, hatching group within the design, and for body weight as a covariable. Univariate analyses confirmed the QTL segregation for AF and BM on GGA5 in male offspring, but not in female offspring. Analyses of male offspring data using multitrait and linked-QTL models led us to conclude the presence of two QTL on the distal part of GGA5, each controlling one trait. Linked QTL models were applied after correction of phenotypic values for the effects of these distal QTL. Several QTL for AF and BM were then discovered in the central region of GGA5, splitting one large QTL region for AF into several distinct QTL. Neither the 'Fat' nor the 'Lean' line appeared to be fixed for any QTL genotype. These results have important implications for prospective fine mapping studies and for the identification of underlying genes and causal mutations.

Microsatellite mapping of QTLs affecting resistance to coccidiosis (Eimeria tenella) in a Fayoumi x White Leghorn cross

Background

Avian coccidiosis is a major parasitic disease of poultry, causing severe economical loss to poultry production by affecting growth and feed efficiency of infected birds. Current control strategies using mainly drugs and more recently vaccination are showing drawbacks and alternative strategies are needed. Using genetic resistance that would limit the negative and very costly effects of the disease would be highly relevant. The purpose of this work was to detect for the first time QTL for disease resistance traits to Eimeria tenella in chicken by performing a genome scan in an F2 cross issued from a resistant Fayoumi line and a susceptible Leghorn line.

Results

The QTL analysis detected 21 chromosome-wide significant QTL for the different traits related to disease resistance (body weight growth, plasma coloration, hematocrit, rectal temperature and lesion) on 6 chromosomes. Out of these, a genome-wide very significant QTL for body weight growth was found on GGA1, five genome-wide significant QTL for body weight growth, plasma coloration and hematocrit and one for plasma coloration were found on GGA1 and GGA6, respectively. Two genome-wide suggestive QTL for plasma coloration and rectal temperature were found on GGA1 and GGA2, respectively. Other chromosme-wide significant QTL were identified on GGA2, GGA3, GGA6, GGA15 and GGA23. Parent-of-origin effects were found for QTL for body weight growth and plasma coloration on GGA1 and GGA3. Several QTL for different resistance phenotypes were identified as co-localized on the same location.

Conclusion

Using an F2 cross from resistant and susceptible chicken lines proved to be a successful strategy to identify QTL for different resistance traits to Eimeria tenella, opening the way for further gene identification and underlying mechanisms and hopefully possibilities for new breeding strategies for resistance to coccidiosis in the chicken. From the QTL regions identified, several candidate genes and relevant pathways linked to innate immune and inflammatory responses were suggested. These results will be combined with functional genomics approaches on the same lines to provide positional candidate genes for resistance loci for coccidiosis. Results suggested also for further analysis, models tackling the complexity of the genetic architecture of these correlated disease resistance traits including potential epistatic effects.

Detecting parent of origin and dominant QTL in a two-generation commercial poultry pedigree using variance component methodology

INTRODUCTION

Variance component QTL methodology was used to analyse three candidate regions on chicken chromosomes 1, 4 and 5 for dominant and parent-of-origin QTL effects. Data were available for bodyweight and conformation score measured at 40 days from a two-generation commercial broiler dam line. One hundred dams were nested in 46 sires with phenotypes and genotypes on 2708 offspring. Linear models were constructed to simultaneously estimate fixed, polygenic and QTL effects. Different genetic models were compared using likelihood ratio test statistics derived from the comparison of full with reduced or null models. Empirical thresholds were derived by permutation analysis.

RESULTS

Dominant QTL were found for bodyweight on chicken chromosome 4 and for bodyweight and conformation score on chicken chromosome 5. Suggestive evidence for a maternally expressed QTL for bodyweight and conformation score was found on chromosome 1 in a region corresponding to orthologous imprinted regions in the human and mouse.

CONCLUSION

Initial results suggest that variance component analysis can be applied within commercial populations for the direct detection of segregating dominant and parent of origin effects.

Polymorphisms of the IGF1R gene and their genetic effects on chicken early growth and carcass traits

BACKGROUND

The insulin-like growth factor I receptor (IGF1R) has an important effect on growth, carcass, and meat quality traits in many species. However, few studies on associations of the IGF1R gene with growth and carcass traits have been reported in chickens. The objectives of the present study were to study the associations of the IGF1R gene with chicken early growth and carcass traits using a neutral test, variation scan of the gene, genetic diversity, linkage disequilibrium and association analyses.

RESULTS

The tree generated from the amino acid sequences of 15 species showed that the IGF1R gene was conservative in the whole evolution among the mammalian animals and chickens. In a total of 10,818 bp of sequence, 70 single nucleotide polymorphisms were identified in the chicken IGF1R gene. The allelic and genotypic frequency distribution, genetic diversity and linkage disequilibrium of 18 single nucleotide polymorphisms (SNPs) in the Xinghua and White Recessive Rock chickens showed that six of them were possibly associated with growth traits. Association analyses showed that the A17299834G SNP was significantly associated with chicken carcass body weight, eviscerated weight with giblets, eviscerated weight, body weights at 28, 35, and 56 d of age, leg length at 56 d of age, and daily weight gain at 0-4 weeks. The haplotypes of the A17307750G and A17307494G were associated with early growth traits. The haplotypes of the A17299834G and C17293932T were significantly associated with most of the early growth traits and carcass traits.

CONCLUSION

There were rich polymorphisms in the chicken IGF1R gene. Several SNPs associated with chicken early growth traits and carcass traits were identified in the IGF1R gene by genetic diversity, linkage disequilibrium, and association analyses in the present study.

The PIT1 gene polymorphisms were associated with chicken growth traits

Background

With crucial roles on the differentiation of anterior pituitary and the regulation of the prolactin (PRL), growth hormone (GH) and thyroid-stimulating hormone-β (TSH-β) genes, the chicken PIT1 gene is regarded as a key candidate gene for production traits. In this study, five reported polymorphisms (MR1-MR5) of the PIT1 gene were genotyped in a full sib F₂ resource population to evaluate their effects on growth, carcass and fatty traits in chickens.

Results

Marker-trait association analyses showed that, MR1 was significantly associated with shank diameters (SD) at 84 days (P < 0.05), hatch weight (HW) and shank length (SL) at 84 days (P < 0.01), MR2 was significantly associated with BW at 28, 42 days and average daily gain (ADG) at 0–4 weeks (P < 0.05), and MR3 was significantly associated with ADG at 4–8 weeks (P < 0.05). MR4 was associated with SL at 63, 77, 84 days and BW at 84 days (P < 0.05), as well as SD at 77 days (P < 0.01). Significant association was also found of MR5 with BW at 21, 35 days and SD at 63 days (P < 0.05), BW at 28 days and ADG at 0–4 weeks (P < 0.01). Both T allele of MR4 and C allele of MR5 were advantageous for chicken growth. The PIT1 haplotypes were significantly associated with HW (P = 0.0252), BW at 28 days (P = 0.0390) and SD at 56 days (P = 0.0400). No significant association of single SNP and haplotypes with chicken carcass and fatty traits was found (P > 0.05).

Conclusion

Our study found that polymorphisms of PIT1 gene and their haplotypes were associated with chicken growth traits and not with carcass and fatty traits.

Identification of quantitative trait loci affecting shank length, body weight and carcass weight from the Japanese cockfighting chicken breed, Oh-Shamo (Japanese Large Game)

We performed a quantitative trait locus (QTL) analysis to map QTLs controlling shank length, body weight, and carcass weight in a resource family of 245 F(2) birds developed from a cross of the large-sized, native, Japanese cockfighting breed, Oh-Shamo (Japanese Large Game), and the White Leghorn breed of chickens. Interval mapping revealed three significant QTLs for shank length on chromosomes 1, 4 and 24 at the experiment-wise 5% level, and a suggestive shank length QTL on chromosome 27 at the experiment-wise 10% level. For body weight two QTLs, one significant and the other suggestive, were identified on chromosomes 4 and 24, respectively. As expected, QTLs for carcass weight, which was highly correlated with body weight (r = 0.95), were detected at the same chromosomal locations as the detected body weight QTLs. Interestingly, the chromosomal locations containing these body weight and carcass weight QTLs coincided with those of two of the four shank length QTLs detected. No QTL with an epistatic interaction effect was discovered for any trait. The total contribution of all detected QTLs to genetic variance was 98.4%, 27.0% and 25.9% for shank length, body weight and carcass weight, respectively, indicating that most shank length QTLs have been identified but many body weight and carcass weight QTLs have been overlooked by the present analysis because of a low coverage rate of the 88 microsatellite markers used here (approximately 46% of the whole genome).

Parent-of-origin specific QTL--a possibility towards understanding reciprocal effects in chicken and the origin of imprinting

Reciprocal effects for sexual maturity, egg production, egg quality traits and viability are well known in poultry crosses. They have been used in an optimal way to form profitable production hybrids. These effects have been hypothesized to originate from sex-linked genes, maternal effects or a combination of both. However, these may not be the only explanations for reciprocal effects. Recent mapping of quantitative trait loci (QTL) has revealed autosomal areas with parent-of-origin specific effects in the chicken. In mammals, parental imprinting, i.e. the specifically regulated expression of either maternal or paternal allele in the offspring, is the main cause of such effects. The most commonly accepted hypothesis for the origin of imprinting, the conflict hypothesis, assumes a genetic conflict of interest between the maternal and paternal genomes regarding the allocation of resources to the offspring. It also intrinsically implies that imprinting should not occur in oviparous taxa. However, new molecular genetic information has raised a need to review the possible involvement of imprinting or some related phenomena as a putative cause of reciprocal effects in poultry. Comparative mapping provides strong evidence for the conservation of orthologous imprinted gene clusters on chicken macrochromosomes. Furthermore, these gene clusters exhibit asynchronous DNA replication, an epigenetic mark specific for all imprinted regions. It has been proposed that these intrinsic chromosomal properties have been important for the evolution of imprinted gene expression in the mammalian lineage. Many of the mapped parent-of-origin specific QTL effects in chicken locate in or close to these conserved regions that show some of the basic features involved in monoallelic expression. If monoallelic expression in these regions would be observed in birds, the actual mechanism and cause may be different from the imprinting that evolved later in the mammalian lineage. In this review we discuss recent molecular genetic results that may provide tools for understanding of reciprocal differences in poultry breeding and the evolution of imprinting.

Genome-wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population

Genome-wide association studies have become possible in the chicken because of the recent availability of the complete genome sequence, a polymorphism map and high-density single nucleotide polymorphism (SNP) genotyping platforms. We used these tools to study the genetic basis of a very high level of heterosis that was previously observed for fatness in two F(2) populations established by crossing one outbred broiler (meat-type) sire with dams from two unrelated, highly inbred, light-bodied lines (Fayoumi and Leghorn). In each F(2) population, selective genotyping was carried out using phenotypically extreme males for abdominal fat percentage (AF) and about 3000 SNPs. Single-point association analysis of about 500 informative SNPs per cross showed significant association (P < 0.01) of 15 and 24 markers with AF in the Broiler x Fayoumi and Broiler x Leghorn crosses respectively. These SNPs were on 10 chromosomes (GGA1, 2, 3, 4, 7, 8, 10, 12, 15 and 27). Interestingly, of the 39 SNPs that were significantly associated with AF, there were about twice as many homozygous genotypes associated with higher AF that traced back to the inbred lines alleles, although the broiler line had on average higher AF. These SNPs are considered to be associated with QTL with cryptic alleles. This study reveals cryptic alleles as an important factor in heterosis for fatness observed in two chicken F(2) populations, and suggests epistasis as the common underlying mechanism for heterosis and cryptic allele expression. The results of this study also demonstrate the power of high marker-density SNP association studies in discovering QTL that were not detected by previous microsatellite-based genotyping studies.

Mapping Quantitative Trait Loci Affecting Body Weight and Abdominal Fat Weight on Chicken Chromosome One

Body weight and abdominal fat traits are complex and important economic traits that may benefit from the implementation of MAS. The objective of the current study was to identify QTL associated with BW and abdominal fat traits. The Northeast Agricultural University resource population was used in the current study. Body weight and abdominal fat weight were measured in the F2 population. A total of 369 F2 individuals produced from 4 F1 families, their parents, and F0 birds were genotyped by 23 fluorescent microsatellite markers on chromosome 1. A linkage map was constructed, and interval mapping was conducted to identify putative QTL. For BW, 10 QTL were identified at the 1% chromosome wide level, and these 10 QTL were grouped to 3 different regions; 2 QTL were identified at the 5% chromosome wide level, and these 2 QTL were grouped to 2 different regions; and 5 QTL were identified at the suggestive level, and these 5 QTL were grouped to 4 different regions. For the abdominal fat traits, 1 QTL was identified at the 1% chromosome wide level, 1 QTL was identified at the 5% chromosome wide level, and 2 QTL were identified at the suggestive level. The QTL for BW at 12 wk of age explained 13.51% of the phenotypic variance, and 2 QTL for abdominal fat weight explained 2.53 and 3.97% of the phenotypic variance, respectively. The present study identified chromosome regions harboring significant QTL affecting BW and abdominal fat traits. The results provide a useful reference for further candidate gene research and MAS for BW and abdominal fat traits.

Review of Quantitative Trait Loci Identified in the Chicken

Methods for mapping QTL are actively used in the chicken to identify chromosomal regions contributing to variation in traits related to growth, disease resistance, egg production, behavior, and metabolic parameters. However, higher-resolution mapping and better knowledge of the genetic architecture underlying QTL are needed for successful application of this information into breeding programs. Therefore, this paper summarizes and integrates original, primary QTL studies in the chicken to identify basic information on the genetic architecture of quantitative traits in chickens. The results of this review show several instances of consensus of QTL locations for similar traits from independent studies. Furthermore, the consensus of QTL location for different traits and evidence for QTL with parent-of-origin effect, transgressive alleles, epistatic QTL, and QTL x sex interaction in chicken are presented and discussed. This information can be helpful in identifying genes or mutations underlying the QTL and in the application of genomic information in marker-assisted breeding programs.

Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. I. Growth and Average Daily Gain

A genome scan was used to detect chromosomal regions and QTL that control quantitative traits of economic importance in chickens. Two unique F(2) crosses generated from a commercial broiler male line and 2 genetically distinct inbred lines (Leghorn and Fayoumi) were used to identify QTL affecting BW and daily average gain traits in chickens. Body weight at 2, 4, 6, and 8 wk was measured in the 2 F(2) crosses. Birds were genotyped for 269 microsatellite markers across the entire genome. Linkage distance among microsatellite markers was estimated by the CRIMAP program. The program QTL Express was used for QTL detection. Significance levels were obtained using the permutation test. For the 8 traits, a total of 18 and 13 significant QTL were detected at a 1% chromosome-wise significance level, of which 17 and 10 were significant at the 5% genome-wise level for the broiler-Leghorn cross and broiler-Fayoumi cross, respectively. Highly correlated growth traits showed similar QTL profiles within each cross but different QTL profiles between the 2 crosses. Most QTL for growth traits in the current study were detected in Gga 1, 2, 4, 7, and 14 for the broiler-Leghorn cross and Gga 1, 2, 4, 5, 8, and 13 for the broiler-Fayoumi cross. Potential candidate genes within the QTL region for growth traits at 1% chromosome-wise significance level were discussed. The results in the current study lay the foundations for fine mapping these traits in the advanced intercross lines and provide a start point for identification causative genes responsible for growth traits in chickens.

Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. II. Body Composition

Two informative chicken F(2) populations based on crosses between a broiler breeder male line and dams from genetically distinct, highly inbred (>99%) chicken lines, the Leghorn G-B2 and Fayoumi M15.2, have been used for genome-wide linkage and QTL analysis. Phenotypic data on 12 body composition traits (breast muscle weight, breast muscle weight percentage, abdominal fat weight, abdominal fat weight percentage, heart weight, heart weight percentage, liver weight, liver weight percentage, spleen weight, spleen weight percentage, and drumstick weight, and drumstick weight percentage) were collected. Birds were genotyped for 269 microsatellite markers across the genome. The QTL Express program was used to detect QTL for body composition traits. Significant levels were obtained using the permutation test. For the twelve traits, a total of 61 (Gga 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 18, 24, and Z) and 45 (Gga 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 17, and E46) significant QTL were detected at the 5% chromosome-wise significance level, of which 19 and 11 were significant at the 5% genome-wise level for the broiler-Leghorn cross and broiler-Fayoumi cross, respectively. Phenotypic variation for each trait explained by all QTL across the genome ranged from 3.22 to 33.31% in the broiler-Leghorn cross and 4.83 to 47.12% in broiler-Fayoumi cross. Distinct QTL profiles between the 2 crosses were observed for most traits. Cryptic alleles were detected for each trait. Potential candidate genes within the QTL region for body composition traits at the 1% chromosome-wise significance level were identified from databases for future association study. The results of the current study will increase the knowledge of genetic markers associated with body composition traits and aid the process of identifying causative genes. Knowledge of beneficial genetic variation can be incorporated in breeding programs to enhance genetic improvement through marker-assisted selection in chickens.