Search

Background: Poultry breeding programs have been focused on improvement of growth and carcass traits, however, this has resulted in correlated changes in internal organ weights and increased incidence of metabolic disorders. These disorders can affect feed efficiency or even cause death. We used a high density SNP array (600 K, Affymetrix) to estimate genomic heritability, perform genome-wide association analysis, and identify genomic regions and positional candidate genes (PCGs) associated with internal organ traits in an F2 chicken population. We integrated knowledge of haplotype blocks, selection signature regions and sequencing data to refine the list of PCGs., Results: Estimated genomic heritability for internal organ traits in chickens ranged from low (LUNGWT, 0.06) to high (GIZZWT, 0.45). A total of 20 unique 1 Mb windows identified on GGA1, 2, 4, 7, 12, 15, 18, 19, 21, 27 and 28 were significantly associated with intestine length, and weights or percentages of liver, gizzard or lungs. Within these windows, 14 PCGs were identified based on their biological functions: TNFSF11, GTF2F2, SPERT, KCTD4, HTR2A, RB1, PCDH7, LCORL, LDB2, NR4A2, GPD2, PTPN11, ITGB4 and SLC6A4. From those genes, two were located within haplotype blocks and three overlapped with selection signature regions. A total of 13,748 annotated sequence SNPs were in the 14 PCGs, including 156 SNPs in coding regions (124 synonymous, 26 non-synonymous, and 6 splice variants). Seven deleterious SNPs were identified in TNFSF11, NR4A2 or ITGB4 genes., Conclusions: The results from this study provide novel insights to understand the genetic architecture of internal organ traits in chickens. The QTL detection performed using a high density SNP array covered the whole genome allowing the discovery of novel QTL associated with organ traits. We identified PCGs within the QTL involved in biological processes that may regulate internal organ growth and development. Potential functional genetic variations were identified generating crucial information that, after validation, might be used in poultry breeding programs to reduce the occurrence of metabolic disorders.

Many economic losses occur in the poultry industry due to leg fragility. Knowing the genomic regions that influence traits associated with the growth and composition of the leg's bone can help to improve the selection process leading to increased leg resistance to fracture. The present study aimed to map quantitative trait loci (QTL) for mineral composition and morphometric traits of the tibia in 478 animals from an F2 broiler × layer cross. The measurement of weight, length and width of Tibia was carried out at 42 days of age. Ash, dry matter, levels of calcium (Ca), phosphorus (P), magnesium (Mg), Zinc (Zn) and Calcium:Phosphorus (Ca:P) ratio were also recorded. The population was genotyped for 128 microsatellite markers and one single nucleotide polymorphism, covering 2630 cM of the chicken genome. A likelihood ratio test was performed to find QTLs. Additive and dominance effects of the QTLs were included in the model. In the chromosomes 2 (GGA2), 6 (GGA6), 8 (GGA8), 24 (GGA24) and 26 (GGA26) some suggestive QTLs (P<0.00276) were mapped for tibia weight (GGA2 and GGA26), ash percentage (GGA2 and GGA6), dry matter percentage (GGA2), Ca (GGA8 and GGA24) and Ca:P ratio (GGA8), many of which are close to genes already identified as good candidates for those traits. The suggestive QTL on GGA2 has a pleiotropic effect on ash percentage, dry matter and bone weight, whereas in the GGA8 there seems to be two QTLs, one for Ca and another for Ca:P ratio. Thus, this study identified at least five genomic regions, in different chromosomes, that can be targeted for further research to identify potential mutations influencing the development and composition of leg bones in Gallus gallus.

Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F 2 chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs., Competing Interests: The authors declare no competing financial interests.

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.

Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 ± 0.18 (between tibia length and BW42) to 0.89 ± 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

Genetic selection for production traits has resulted in a rapid improvement in animal performance and development. Previous studies have mapped quantitative trait loci for body weight at 35 and 41 days, and drum and thigh yield, onto chicken chromosome 4. We investigated this region for single nucleotide polymorphisms and their associations with important economic traits. Three positional candidate genes were studied: KLF3 (Krüeppel-like factor 3), SLIT2 (Slit homolog 2), and PPARGC1A (peroxisome proliferator-activated receptor gamma, coactivator 1 alpha). Fragment sequencing of these genes was conducted in 11 F1 animals, and one polymorphism in each gene was selected and genotyped in an F2 population (N = 276) and a paternal broiler line TT (N = 840). Associations were identified with growth, carcass, and fat traits in the F2 and the paternal line (P < 0.05). Using single markers in both the F2 and the TT line, KLF3 was associated with weight gain (P < 0.05), PPPARGC1A was associated with liver and wing-parts weights and yields (P < 0.05), and SLIT2 was associated with back yield (P < 0.05) and fat traits (P < 0.05). Using multiple markers, KLF3 lost its significance in both populations, and SLIT2 was associated with feed conversion only in the TT population (P < 0.05). The QTLs mapped in the F2 population could be partly explained by PPARGC1A and SLIT2, which were associated with body weight at 35 and 41 days, respectively, and with drum and thigh yield in the same population. The results of this study indicate the importance of these genes for production traits.

Apolipoprotein B (APOB) and Adiponectin Receptor 1 (ADIPOR1) are related to the regulation of feed intake, fat metabolism and protein deposition and are candidate genes for genomic studies in birds. In this study, associations of two single nucleotide polymorphisms (SNPs) g.102A>T (APOB) and g.729C>T (ADIPOR1) with carcass, bone integrity and performance traits in broilers were investigated. Genotyping was performed on a paternal line of 1,454 broilers. The SNP detection was carried out by PCR-RFLP technique using the restriction enzymes HhaI for the SNP g.729C>T and MslI for the SNP g.102A>T. The association analyses of the two SNPs with 85 traits were performed using the restricted maximum likelihood (REML) and Generalized Quasi-Likelihood Score (GQLS) methods. For REML the model included the random additive genetic effect of animal and fixed effects of sex, hatch and SNP genotypes. In the GQLS method, a logistic regression was used to associate the genotypes with phenotypes adjusted for fixed effects of sex and hatch. The SNP g.729C>T in the ADIPOR1 gene was associated with thickness of the femur and breast skin yield. Thus, the ADIPOR1 gene seems implicated in the metabolism and/or fat deposition and bone integrity in broilers.

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., (© 2015 Stichting International Foundation for Animal Genetics.)

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., (© 2015 Stichting International Foundation for Animal Genetics.)

Interval mapping (IM) implemented in QTL Express or GridQTL is widely used, but presents some limitations, such as restriction to a fixed model, risk of mapping two QTL when there may be only one and no discrimination of two or more QTL using both cofactors located on the same and other chromosomes. These limitations were overcome with composite interval mapping (CIM). We reported QTL associated with performance and carcass traits on chicken chromosomes 1, 3, and 4 through implementation of CIM and analysis of phenotypic data using mixed models. Thirty-four microsatellite markers were used to genotype 360 F2 chickens from crosses between males from a layer line and females from a broiler line. Sixteen QTL were mapped using CIM and 14 QTL with IM. Furthermore, of those 30 QTL, six were mapped only when CIM was used: for body weight at 35 days (first and third peaks on GGA4), body weight at 41 days (GGA1B and second peak on GGA4), and weights of back and legs (both on GGA4). Three new regions had evidence for QTL presence: one on GGA1B associated with feed intake 35-41 d at 404 cM (LEI0107-ADL0183) and two on GGA4 associated with weight of back at 163 cM (LEI0076-MCW0240) and weight gain 35-41 d, feed efficiency 35-41 d and weight of legs at 241 cM (LEI0085-MCW0174). We dissected one more linked QTL on GGA4, where three QTL for BW35 and two QTL for BW41 were mapped. Therefore, these new regions mapped here need further investigations using high-density SNP to confirm these QTL and identify candidate genes associated with those traits.

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., (© 2012 The Authors, Animal Genetics © 2012 Stichting International Foundation for Animal Genetics.)

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., (© 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.)

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.

With the objective of mapping quantitative trait loci (QTLs) for performance and carcass traits, an F2 chicken population was developed by crossing broiler and layer lines. A total of 2063 F2 chicks in 21 full-sib families were reared as broilers and slaughtered at 42 days of age. Seventeen performance and carcass traits were measured. Parental F(0) and F1 individuals were genotyped with 80 microsatellites from chicken chromosome 1 to select informative markers. Thirty-three informative markers were used for selective genotyping of F2 individuals with extreme phenotypes for body weight at 42 days of age (BW42). Based on the regions identified by selective genotyping, seven full-sib families (649 F2 chicks) were genotyped with 26 markers. Quantitative trait loci affecting body weight, feed intake, carcass weight, drums and thighs weight and abdominal fat weight were mapped to regions already identified in other populations. Quantitative trait loci for weights of gizzard, liver, lungs, heart and feet, as well as length of intestine, not previously described in the literature were mapped on chromosome 1. This F2 population can be used to identify novel QTLs and constitutes a new resource for studies of genes related to growth and carcass traits in poultry.