Chromosome-wise Significance Level Research Articles

Genome-Wide Association Study Demonstrates the Role Played by the CD226 Gene in Rasa Aragonesa Sheep Reproductive Seasonality.

Simple SummaryTo elucidate the genetic basis of reproductive seasonality in Rasa Aragonesa sheep breed, we performed a genome-wide association study (GWAS) in order to detect single nucleotide polymorphisms (SNPs) or regions associated with traits related to ovarian function and behavioural signs of estrous. The GWAS included 205 ewes with genotypes for 583882 SNPs. Only one SNP overcame the genome-wide significance level. Nine potential SNPs overcame the chromosome-wise significance level (FDR 10%). Gene annotation demonstrated that CD226 molecule (CD226) and neuropeptide Y (NPY) genes that could be involved in reproductive seasonality were close to the significant SNPs. To validate the results, we sequenced the entire coding region of the NPY gene and four exons of the CD226 gene to search for polymorphisms that could be involved in the phenotypes studied. Two synonymous and two nonsynonymous SNPs in the NPY and CD226 genes, respectively, were genotyped in the whole population. We demonstrated that the AA genotype of the SNP rs404360094 located in exon 3 of the CD226 gene was associated with higher and lower total days of anoestrus and oestrous cycling months, respectively. Therefore, this SNP could be utilized as a genetic marker for assisted selection marker to reduce seasonality.A genome-wide association study (GWAS) was used to identify genomic regions influencing seasonality reproduction traits in Rasa Aragonesa sheep. Three traits associated with either ovarian function based on blood progesterone levels (total days of anoestrus and progesterone cycling months) or behavioral signs of oestrous (oestrous cycling months) were studied. The GWAS included 205 ewes genotyped using the 50k and 680k Illumina Ovine Beadchips. Only one SNP associated with the progesterone cycling months overcame the genome-wide significance level (rs404991855). Nine SNPs exhibited significant associations at the chromosome level, being the SNPs rs404991855 and rs418191944, that are located in the CD226 molecule (CD226) gene, associated with the three traits. This gene is related to reproductive diseases. Two other SNPs were located close to the neuropeptide Y (NPY) gene, which is involved in circadian rhythms. To validate the GWAS, partial characterization of both genes by Sanger sequencing, and genotyping of two synonymous and two nonsynonymous SNPs in the NPY and CD226 genes, respectively, were performed. SNP association analysis showed that only SNP rs404360094 in the exon 3 of the CD226 gene, which produces an amino acid substitution from asparagine (uncharged polar) to aspartic acid (acidic), was associated with the three seasonality traits. Our results suggest that the CD226 gene may be involved in the reproductive seasonality in Rasa Aragonesa.

Quantitative Trait Loci Associated with Egg Traits in F2 Intercross between Golden Montazah and White Leghorn Chickens

Quantitative trait loci (QTL) affecting age at first egg (AFE), weight at first egg (WFE), 120-days of egg number (EN), egg weight (EW), Hugh unit (HU) and egg shell strength (ESS) were identified in F2 intercross population produced by crossing males of Golden Montazah (M) with females of White Leghorn (L). Phenotypic data for egg traits of 4131 hens were analyzed using multi-traits animal model. For QTL analysis, 1011 hens of F2 were genotyped using 45 genetic markers in nine autosomal linkage groups and Z chromosome and the mixed model including the fixed effects of hatch along with the additive and dominance effects of QTL as random effects was used. The total map length was 1949 cM and a total of 15 significant QTL were detected for egg traits and these QTL were distributed over four distinct regions on five chromosomes (2, 3, 4, 8 and Z). The QTL region on the Z chromosome was large and including QTL for AFW, EW, EN and ESS. The significant QTL were located on chromosomes 2, 4, 8 and Z for WFE at position of 322, 156, 61 and 102 cM; on the chromosomes 3 and Z for AFE at position of 189 and 128 cM, on the chromosomes 4 and Z sex chromosome for EW at position of 191 and 76 cM; on the chromosomes 4 and Z for EN at position of 55 and 89 cM; on the chromosomes 2, 4 and 8 for HU at position of 89, 222, and 18 cM; on Z sex chromosome for ESS at position of 97 cM, respectively. A total of four significant QTL were detected at 5 % chromosome-wise significance level, while a total of 11 significant QTL were detected at 1 % genomic-wise significance level and the total variances explained by QTL were 10.7, 12.2, 18.6, 12.2, 15.3 and 5 % for WFE, AFE, EW, EN, HU and ESS, respectively. The additive effects attributable to QTL explaining 5.4 to 53.0 % for WFE, 1.6 % for AFE, 4.4 to 8.2 % for EN, 3.0 to 6.5 % for EW, -0.6 and -6.2 % for Hu and -55.6 % for ESS of the total phenotypic variance of the F2 population, while the dominance effects attributable to QTL explained 0.3 to 10.5, 4.0, -1.1 to -18.0, -1.6, -3.9 to -5.3 for WFE, AFE, EN, EW and HU, respectively

Genome-Wide Association Study for Cytokines and Immunoglobulin G in Swine

Increased disease resistance through improved immune capacity would be beneficial for the welfare and productivity of farm animals. To identify genomic regions responsible for immune capacity traits in swine, a genome-wide association study was conducted. In total, 675 pigs were included. At 21 days of age, all piglets were vaccinated with modified live classical swine fever vaccine. Blood samples were sampled when the piglets were 20 and 35 days of age, respectively. Four traits, including Interferon-gamma (IFN-γ) and Interleukin 10 (IL-10) levels, the ratio of IFN-γ to IL-10 and Immunoglobulin G (IgG) blocking percentage to CSFV in serum were measured. All the samples were genotyped for 62,163 single nucleotide polymorphisms (SNP) using the Illumina porcineSNP60k BeadChip. After quality control, 46,079 SNPs were selected for association tests based on a single-locus regression model. To tackle the issue of multiple testing, 10,000 permutations were performed to determine the chromosome-wise and genome-wise significance level. In total, 32 SNPs with chromosome-wise significance level (including 4 SNPs with genome-wise significance level) were identified. These SNPs account for 3.23% to 13.81% of the total phenotypic variance individually. For the four traits, the numbers of significant SNPs range from 5 to 15, which jointly account for 37.52%, 82.94%, 26.74% and 24.16% of the total phenotypic variance of IFN-γ, IL-10, IFN-γ/IL-10, and IgG, respectively. Several significant SNPs are located within the QTL regions reported in previous studies. Furthermore, several significant SNPs fall into the regions which harbour a number of known immunity-related genes. Results herein lay a preliminary foundation for further identifying the causal mutations affecting swine immune capacity in follow-up studies.

Genome-wide association studies for growth and meat production traits in sheep.

BackgroundGrowth and meat production traits are significant economic traits in sheep. The aim of the study is to identify candidate genes affecting growth and meat production traits at genome level with high throughput single nucleotide polymorphisms (SNP) genotyping technologies.Methodology and ResultsUsing Illumina OvineSNP50 BeadChip, we performed a GWA study in 329 purebred sheep for 11 growth and meat production traits (birth weight, weaning weight, 6-month weight, eye muscle area, fat thickness, pre-weaning gain, post-weaning gain, daily weight gain, height at withers, chest girth, and shin circumference). After quality control, 319 sheep and 48,198 SNPs were analyzed by TASSEL program in a mixed linear model (MLM). 36 significant SNPs were identified for 7 traits, and 10 of them reached genome-wise significance level for post-weaning gain. Gene annotation was implemented with the latest sheep genome Ovis_aries_v3.1 (released October 2012). More than one-third SNPs (14 out of 36) were located within ovine genes, others were located close to ovine genes (878bp-398,165bp apart). The strongest new finding is 5 genes were thought to be the most crucial candidate genes associated with post-weaning gain: s58995.1 was located within the ovine genes MEF2B and RFXANK, OAR3_84073899.1, OAR3_115712045.1 and OAR9_91721507.1 were located within CAMKMT, TRHDE, and RIPK2 respectively. GRM1, POL, MBD5, UBR2, RPL7 and SMC2 were thought to be the important candidate genes affecting post-weaning gain too. Additionally, 25 genes at chromosome-wise significance level were also forecasted to be the promising genes that influencing sheep growth and meat production traits.ConclusionsThe results will contribute to the similar studies and facilitate the potential utilization of genes involved in growth and meat production traits in sheep in future.

GWA Analysis for Milk Production Traits in Dairy Sheep and Genetic Support for a QTN Influencing Milk Protein Percentage in the LALBA Gene

In this study, we used the Illumina OvineSNP50 BeadChip to conduct a genome-wide association (GWA) analysis for milk production traits in dairy sheep by analyzing a commercial population of Spanish Churra sheep. The studied population consisted of a total of 1,681 Churra ewes belonging to 16 half-sib families with available records for milk yield (MY), milk protein and fat yields (PY and FY) and milk protein and fat contents (PP and FP). The most significant association identified reached experiment-wise significance for PP and FP and was located on chromosome 3 (OAR3). These results confirm the population-level segregation of a previously reported QTL affecting PP and suggest that this QTL has a significant pleiotropic effect on FP. Further associations were detected at the chromosome-wise significance level on 14 other chromosomal regions. The marker on OAR3 showing the highest significant association was located at the third intron of the alpha-lactalbumin (LALBA) gene, which is a functional and positional candidate underlying this association. Sequencing this gene in the 16 Churra rams of the studied resource population identified additional polymorphisms. One out of the 31 polymorphisms identified was located within the coding gene sequence (LALBA_g.242T>C) and was predicted to cause an amino acid change in the protein (Val27Ala). Different approaches, including GWA analysis, a combined linkage and linkage disequilibrium study and a concordance test with the QTL segregating status of the sires, were utilized to assess the role of this mutation as a putative QTN for the genetic effects detected on OAR3. Our results strongly support the polymorphism LALBA_g.242T>C as the most likely causal mutation of the studied OAR3 QTL affecting PP and FP, although we cannot rule out the possibility that this SNP is in perfect linkage disequilibrium with the true causal polymorphism.

Genome-wide association study for T lymphocyte subpopulations in swine

BackgroundLymphocytes act as a major component of the adaptive immune system, taking very crucial responsibility for immunity. Differences in proportions of T-cell subpopulations in peripheral blood among individuals under same conditions provide evidence of genetic control on these traits, but little is known about the genetic mechanism of them, especially in swine. Identification of the genetic control on these variants may help the genetic improvement of immune capacity through selection.ResultsTo identify genomic regions responsible for these immune traits in swine, a genome-wide association study was conducted. A total of 675 pigs of three breeds were involved in the study. At 21 days of age, all individuals were vaccinated with modified live classical swine fever vaccine. Blood samples were collected when the piglets were 20 and 35 days of age, respectively. Seven traits, including the proportions of CD4+, CD8+, CD4+CD8+, CD4+CD8−, CD4−CD8+, CD4−CD8− and the ratio of CD4+ to CD8+ T cells were measured at the two ages. All the samples were genotyped for 62,163 single nucleotide polymorphisms (SNP) using the Illumina porcineSNP60k BeadChip. 40833 SNPs were selected after quality control for association tests between SNPs and each immune trait considered based on a single-locus regression model. To tackle the issue of multiple testing in GWAS, 10,000 permutations were performed to determine the chromosome-wise and genome-wise significance levels of association tests. In total, 61 SNPs with chromosome-wise significance level and 3 SNPs with genome-wise significance level were identified. 27 significant SNPs were located within the immune-related QTL regions reported in previous studies. Furthermore, several significant SNPs fell into the regions harboring known immunity-related genes, 14 of them fell into the regions which harbor some known T cell-related genes.ConclusionsOur study demonstrated that genome-wide association studies would be a feasible way for revealing the potential genetics variants affecting T-cell subpopulations. Results herein lay a preliminary foundation for further identifying the causal mutations underlying swine immune capacity in follow-up studies.

Identification of a 3.7‐Mb region for a marbling QTL on bovine chromosome 4 by identical‐by‐descent and association analysis

QTL mapping for growth and carcass traits was performed using a paternal half-sib family composed of 325 Japanese Black cattle offspring. Nine QTL were detected at the 1% chromosome-wise significance level at a false discovery rate of less than 0.1. These included two QTL for marbling on BTA 4 and 18, two QTL for carcass weight on BTA 14 and 24, two QTL for longissimus muscle area on BTA 1 and 4, two QTL for subcutaneous fat thickness on BTA 1 and 15 and one QTL for rib thickness on BTA 6. Although the marbling QTL on BTA 4 has been replicated with significant linkages in two Japanese Black cattle sires, the three Q (more marbling) haplotypes, each inherited maternally, were apparently different. To compare the three Q haplotypes in more detail, high-density microsatellite markers for the overlapping regions were developed within the 95% CIs (65 markers in 44-78 cM). A detailed haplotype comparison indicated that a small region (<3.7 Mb) around 46 cM was shared between the Qs of the two sires, whose dams were related. An association of this region with marbling was shown by a regression analysis using the local population, in which the two sires were produced and this was confirmed by an association study using a population collected throughout Japan. These results strongly suggest that the marbling QTL on BTA 4 is located in the 3.7-Mb region at around 46 cM.

A Whole-Genome Scan to Map Quantitative Trait Loci for Conformation and Functional Traits in Canadian Holstein Bulls

Genetic improvement of livestock populations can be achieved through detection and mapping of genetic markers linked to quantitative trait loci (QTL). With the completion of the bovine genome sequence assembly, single nucleotide polymorphism (SNP) assays spanning the whole bovine genome and research work on large-scale identification, validation, and analysis of genotypic variation in cattle has become possible. A total of 462 Canadian Holstein Bulls were used to test the association between SNP and QTL. Single locus linkage disequilibrium regression model was implemented to perform a whole genome scan to identify and map QTL affecting conformation and functional traits. One thousand five hundred thirty-six SNP markers from introns and exons of potential QTL regions for economically important traits across the bovine genome were selected for association analysis. A total of 45 and 151 SNP were found to be associated with 17 conformation and functional traits at a genome- and chromosome-wise significance level, respectively. Among the 196 significant SNP, 169 of them are newly detected in this study, whereas 27 of them have been reported in previous literature and 161 of these were located in genes and are worth further investigating to potentially identify the causative mutations underlying the QTL. The single locus linkage disequilibrium regression method using SNP marker genotypes has proven to be a successful methodology for detecting and mapping QTL in dairy cattle populations.

Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. IV. Metabolic Traits

The current study is a comprehensive genome analysis to detect QTL affecting metabolic traits 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 in the present study. The plasma glucagon, insulin, lactate, glucose, tri-iodothyronine, thyroxine, insulin-like growth factor I, and insulin-like growth factor II concentrations at 8 wk were measured in the 2 F(2) crosses. Birds were genotyped for 269 microsatellite markers across the entire genome. The program QTL Express was used for QTL detection. Significance levels were obtained using the permutation test. For the 10 traits, a total of 6 and 9 significant QTL were detected at a 1% chromosome-wise significance level, of which 1 and 6 were significant at the 5% genome-wise level for the broiler-Leghorn cross and broiler-Fayoumi cross, respectively. Most QTL for metabolic traits in the present study were detected in Gga 2, 6, 8, 9, 13, and Z for the broiler-Leghorn cross and Gga 1, 2, 4, 7, 8, 13, 17, and E47 for the broiler-Fayoumi cross. Phenotypic variation for each trait explained by all QTL across genome ranged from 2.73 to 14.08% in the broiler-Leghorn cross and from 6.93 to 21.15% in the broiler-Fayoumi cross. Several positional candidate genes within the QTL region for metabolic traits at the 1% chromosome-wise significance level are biologically associated with the regulation of metabolic pathways of insulin, triiodothyronine, and thyroxine.

Identification of bovine QTL for growth and carcass traits in Japanese Black cattle by replication and identical-by-descent mapping

To map quantitative trait loci (QTL) for growth and carcass traits in a purebred Japanese Black cattle population, we conducted multiple QTL analyses using 15 paternal half-sib families comprising 7860 offspring. We identified 40 QTL with significant linkages at false discovery rates of less than 0.1, which included 12 for intramuscular fat deposition called marbling and 12 for cold carcass weight or body weight. The QTL each explained 2%-13% of the phenotypic variance. These QTL included many replications and shared hypothetical identical-by-descent (IBD) alleles. The QTL for CW on BTA14 was replicated in five families with significant linkages and in two families with a 1% chromosome-wise significance level. The seven sires shared a 1.1-Mb superior Q haplotype as a hypothetical IBD allele that corresponds to the critical region previously refined by linkage disequilibrium mapping. The QTL for marbling on BTA4 was replicated in two families with significant linkages. The QTL for marbling on BTA6, 7, 9, 10, 20, and 21 and the QTL for body weight on BTA6 were replicated with 1% and/or 5% chromosome-wise significance levels. There were shared IBD Q or q haplotypes in the marbling QTL on BTA4, 6, and 10. The allele substitution effect of these haplotypes ranged from 0.7 to 1.2, and an additive effect between the marbling QTL on BTA6 and 10 was observed in the family examined. The abundant and replicated QTL information will enhance the opportunities for positional cloning of causative genes for the quantitative traits and efficient breeding using marker-assisted selection.

Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. III. Skeletal Integrity

Two unique chicken F(2) populations generated from a broiler breeder male line and 2 genetically distinct inbred (>99%) chicken lines (Leghorn and Fayoumi) were used for whole genome QTL analysis. Twelve phenotypic skeletal integrity traits (6 absolute and 6 relative traits) were measured or calculated, including bone mineral content, bone mineral density, tibia length, shank length, shank weight, and shank length:shank weight. All traits were also expressed as a percentage of BW at 8 wk of age. Birds were genotyped for 269 microsatellite markers across the entire genome. The QTL affecting bone traits in chickens were detected by the QTL express program. Significance levels were obtained using the permutation test. For the 12 traits, a total of 56 significant QTL were detected at the 5% chromosome-wise significance level, of which 14 and 10 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 detected QTL across the genome ranged from 12.0 to 35.6% in the broiler-Leghorn cross and 2.9 to 31.3% in the broiler-Fayoumi cross. Different QTL profiles identified between the 2 related F(2) crosses for most traits suggested that genetic background is an important factor for QTL analysis. Study of associations of biological candidate genes with skeletal integrity traits in chickens will reveal new knowledge of understanding biological process of skeletal homeostasis. The results of the current study have identified markers for bone strength traits, which may be used to genetically improve skeletal integrity in chickens by MAS, and to identify the causal genes for these traits.

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.

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.

Identification of quantitative trait loci for carcass composition and pork quality traits in a commercial finishing cross1

A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Piétrain/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4 traits), carcass composition (11 traits), and meat quality (15 traits). Offspring of 8 sires (n = 715) were used for linkage analysis and genotyped for 73 microsatellite markers covering 14 chromosomal regions representing approximately 50% of the pig genome. The regions examined were selected based on previous studies suggesting the presence of QTL affecting carcass composition or meat quality traits. Thirty-two QTL exceeding the 5% chromosome-wise significance level were identified. Among these, 5 QTL affecting 5 different traits were significant at the 1% chromosome-wise level. The greatest significance levels were found for a QTL affecting loin weight on SSC11 and a QTL with an effect on the Japanese color scale score of the loin on SSC4. About one-third of the identified QTL were in agreement with QTL previously reported. Results showed that QTL affecting carcass composition and meat quality traits segregated within commercial lines. Use of these results for marker-assisted selection offers opportunities for improving pork quality by within-line selection.

High‐resolution physical mapping and construction of a porcine contig spanning the intramuscular fat content QTL

We previously mapped a locus for porcine intramuscular fat content (IMF) by linkage analysis to a 17.1-cM chromosome interval on Sus scrofa chromosome 7 (SSC7) flanked by microsatellite markers SW1083 and SW581. In this study, we identified 34 microsatellite markers and 14 STSs from the 17.1-cM IMF quantitative trait loci (QTL) region corresponding to HSA14q and aligned those loci using the INRA-University of Minnesota porcine radiation hybrid (IMpRH) panel. We then constructed a 5.2-Mb porcine bacterial artificial chromosome (BAC) contig of this region that was aligned using the RH panel. Finally, the IMF QTL was fine-mapped to 12.6 cM between SJ169 and MM70 at the 0.1% chromosome-wise significance level by genotyping the previously studied F2 resource family with 17 additional microsatellites. We also demonstrated that the SJ169-MM70 interval spans approximately 3.0 Mb and contains at least 12 genes: GALC, GPR65, KCNK10, SPATA7, PTPN21, FLJ11806, EML5, TTC8, CHES1, CAP2P1, CHORDC2P and C14orf143.

Whole genome scan for quantitative trait loci affecting body weight in chickens using a three generation design

An experimental population containing 10 full sib families of a cross between two broiler lines was created. In this population blood samples from 20 full sib animals in generation 1 and 451 full sib animals in generation 2 were used for marker genotyping. Data on body weight at slaughter age (48 days) collected in a feed conversion experiment with 2049 individually housed grandoffspring was analysed. Large differences in mean and variance between male and female body weight were found. To account for these differences, a bivariate analysis treating body weight of males and females as separate traits was used to estimate (co)variance components and breeding values. The model accounted for systematic environmental effects and maternal effects. The estimated heritability of body weight was 0.28 in the males and 0.33 in the females and the genetic correlation between male and female body weight did not significantly deviate from unity. Estimated breeding values, fixed and maternal genetic effects were used to calculate average adjusted progeny trait values for all generation 2 animals adjusted for fixed and maternal genetic effects and for the additive genetic contribution of the other parent. Male and female progeny trait values were combined in one trait value adjusting for sex differences by standardisation for mean and variance. This average adjusted progeny trait value was used for QTL detection. To study presence of QTLs, an across family weighted regression interval mapping approach was used both in half sib as well as a full sib QTL analysis. Genotypes from 368 markers mapped on 24 autosomal linkage groups were available. The most likely position for a QTL affecting body weight was found on chromosome 1 at 240 cM with a test statistic of 2.32. Significance levels were obtained using the permutation test. The chromosomewise significance level of this QTL was 10%, whereas the genomewise significance level was 41%. New aspects of this study are: Genomewide QTL analysis in poultry, full sib analysis in an outbred population structure and correction for heterogeneous variances between sexes.