Joint analysis of two breed cross populations in pigs to improve detection and characterization of quantitative trait loci1

Using genome wide association studies to identify common QTL regions in three different genetic backgrounds based on Iberian pig breed

One of the major limitation for the application of QTL results in pig breeding and QTN identification has been the limited number of QTL effects validated in different animal material. The aim of the current work was to validate QTL regions through joint and specific genome wide association and haplotype analyses for growth, fatness and premier cut weights in three different genetic backgrounds, backcrosses based on Iberian pigs, which has a major role in the analysis due to its high productive relevance. The results revealed nine common QTL regions, three segregating in all three backcrosses on SSC1, 0–3 Mb, for body weight, on SSC2, 3–9 Mb, for loin bone-in weight, and on SSC7, 3 Mb, for shoulder weight, and six segregating in two of the three backcrosses, on SSC2, SSC4, SSC6 and SSC10 for backfat thickness, shoulder and ham weights. Besides, 18 QTL regions were specifically identified in one of the three backcrosses, five identified only in BC_LD, seven in BC_DU and six in BC_PI. Beyond identifying and validating QTL, candidate genes and gene variants within the most interesting regions have been explored using functional annotation, gene expression data and SNP identification from RNA-Seq data. The results allowed us to propose a promising list of candidate mutations, those identified in PDE10A, DHCR7, MFN2 and CCNY genes located within the common QTL regions and those identified near ssc-mir-103-1 considered PANK3 regulators to be further analysed.

Genome-wide association study in an F2 Duroc x Pietrain resource population for economically important meat quality and carcass traits

Meat quality is essential for consumer acceptance, it ultimately impacts pork production profitability and it is subject to genetic control. The objective of this study was to map genomic regions associated with economically important meat quality and carcass traits. We performed a genome-wide association (GWA) analysis to map regions associated with 38 meat quality and carcass traits recorded for 948 F2 pigs from the Michigan State University Duroc × Pietrain resource population. The F0, F1, and 336 F2 pigs were genotyped with the Illumina Porcine SNP60 BeadChip, while the remaining F2 pigs were genotyped with the GeneSeek Genomic Profiler for Porcine Low Desnisty (LD) chip, and imputed with high accuracy ( = 0.97). Altogether the genomic dataset comprised 1,019 animals and 44,911 SNP. A Gaussian linear mixed model was fitted to estimate the breeding values and the variance components. A linear transformation was performed to estimate the marker effects and variances. Type I error rate was controlled at a False Discovery Rate of 5%. Seven putative QTL found in this study were previously reported in other studies. Two novel QTL associated with tenderness (TEN) were located on SSC3 [135.6:137.5Mb; False Discovery rate (FDR) < 0.03] and SSC5 (67.3:69.1Mb; FDR < 0.02). The QTL region identified on SSC15 includes Protein Kinase AMP-activated ɣ 3-subunit gene (), which has been associated with 24-h pH (pH24), drip loss (DL) and cook yield (CY). Also, novel candidate genes were identified for TEN in the region on SSC5 [A Kinase (PRKA) Anchor Protein 3 (], and for tenth rib backfat thickness (BF10) [Carnitine O-Acetyltransferase ()] on SSC1. The association of gene polymorphisms with pork quality traits has been reported for several pig populations. However, there are no SNP for this gene on the chip used, thus we genotyped the animals for 2 non-synonymous variants ( and ). We then performed a GWA conditioning on the genotype of both SNP and was associated with pH24, DL, protein content (PRO) and CY ( < 0.004) and T30N with Juiciness, TEN, shear force, pH24, PRO, and CY < 0.04). Finally, we performed a GWA conditioning on the genotype of the SNP peak detected in this study, and T30N remained associated only with PRO ( < 0.02). Therefore, in this study we identified 2 novel QTL regions, suggest 2 novel candidate genes, and conclude that other SNP in PRKAG3 or nearby gene(s) explain the observed associations on SSC15 in this population.

Meta-analysis of genome-wide association from genomic prediction models

Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.

A study of vertebra number in pigs confirms the association of vertnin and reveals additional QTL

Background

Formation of the vertebral column is a critical developmental stage in mammals. The strict control of this process has resulted in little variation in number of vertebrae across mammalian species and no variation within most mammalian species. The pig is quite unique as considerable variation exists in number of thoracic vertebrae as well as number of lumbar vertebrae. At least two genes have been identified that affect number of vertebrae in pigs yet considerable genetic variation still exists. Therefore, a genome-wide association (GWA) analysis was conducted to identify additional genomic regions that affect this trait.

Results

A total of 1883 animals were phenotyped for the number of ribs and thoracolumbar vertebrae as well as successfully genotyped with the Illumina Porcine SNP60 BeadChip. After data editing, 41,148 SNP markers were included in the GWA analysis. These animals were also phenotyped for kyphosis. Fifty-three 1 Mb windows each explained at least 1.0 % of the genomic variation for vertebrae counts while 16 regions were significant for kyphosis. Vertnin genotype significantly affected vertebral counts as well. The region with the largest effect for number of lumbar vertebrae and thoracolumbar vertebrae were located over the Hox B gene cluster and the largest association for thoracic vertebrae number was over the Hox A gene cluster. Genetic markers in significant regions accounted for approximately 50 % of the genomic variation. Less genomic variation for kyphosis was described by QTL regions and no region was associated with kyphosis and vertebra counts.

Conclusions

The importance of the Hox gene families in vertebral development was highlighted as significant associations were detected over the A, B and C families. Further evaluation of these regions and characterization of variants within these genes will expand our knowledge on vertebral development using natural genetic variants segregating in commercial swine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0286-9) contains supplementary material, which is available to authorized users.

Identification and characterization of a differentially expressed protein (CAPZB) in skeletal muscle between Meishan and Large White pigs

Actin capping protein beta (CAPZB) protein was identified with considerable differences in the longissimus dorsi muscle between Large White and Meishan pigs using proteomics approach. However, in pigs, the information on CAPZB is very limited. In this study, we cloned and characterized the porcine actin capping protein beta (CAPZB) gene. In addition, we present two novel porcine CAPZB splice variants CAPZB1 and CAPZB2. CAPZB1 was expressed in all twenty tissues. However, CAPZB2 was predominantly expressed in the skeletal muscle and heart. In addition, the two isoforms had different expression profiles during the skeletal muscle development and between breeds. Moreover, the SNP T394G was identified in the coding region of the CAPZB gene, which was significantly associated with the carcass traits including the LFW, CFW, SFT and LEA. Data presented in our study suggests that the CAPZB gene may be a candidate gene of meat production trait and provides useful information for further studies on its roles in porcine skeletal muscle.

Investigation of four candidate genes (IGF2, JHDM1A, COPB1 and TEF1) for growth rate and backfat thickness traits on SSC2q in Large White pigs

As important quantitative traits, the growth rate and backfat thickness are controlled by multiple genes. The aim of this investigation was to evaluate the effect of the single and multiple SNPs of four candidate genes (IGF2, JHDM1A, COPB1 and TEF-1) on growth rate and backfat thickness. The four candidate genes were mapped on the p arm of SSC 2, and there are several QTLs, such as average daily gain, backfat thickness, an imprinted QTLs affecting muscle mass and fat deposition have been reported in this region. The polymorphisms of these genes were detected using PCR-RFLP methods, mixed procedure was used to analyze the single marker association with the growth and backfat thickness traits, and the gene-gene combination was investigated using multiple-markers analysis. The single marker association analysis indicated that the IGF2 intron-3 g.3072G > A and the substitution g.93G > A of TEF-1 gene were significantly associated with the age at 100 kg (P < 0.05). The JHDM1A 3′UTR g.224C > G, the c.3096C > T polymorphism of COPB1 gene and the substitution g.93G > A of TEF-1 gene were all significantly associated with the backfat at the shoulder (P < 0.05), backfat at the last rib, backfat at the lumbar, and the average backfat thickness, respectively. The multiple-markers analysis indicated that IGF2 and TEF-1 integrated gene networks for the age at 100 kg. Therefore, we can suggest that the polymorphism of IGF2 and TEF-1 gene could be used in marker-assisted selection for the age at 100 kg in Large White pigs.

Molecular characterization, expression patterns, and polymorphism of a differentially expressed porcine gene (PYGM) isolated by suppression subtractive hybridization and two-dimensional gel electrophoresis analysis

Suppression subtractive hybridization was performed to detect the differences in gene expression of porcine longissimus dorsi muscles between Large White and Chinese Meishan pigs. An upregulated gene in Large White that shared high homology with human muscle glycogen phosphorylase (PYGM) was identified. The porcine PYGM gene contains an open reading frame encoding 842 amino acid residues with 26 and 283 nucleotides in the 5' and 3' untranslated regions, respectively. Tissue distribution analysis indicated that porcine PYGM mRNAs are highly expressed in all tissues. Expression pattern of PYGM was similar in the two breeds. Both breeds had the highest expression levels when 120 days old (p<0.01), and PYGM was upregulated during skeletal muscle development. A similar expression pattern of PYGM in protein level was also observed by differential proteome analysis of skeletal muscle development using two-dimensional gel electrophoresis and mass spectroscopy. The mRNA abundance of PYGM in Large White was higher than Meishan at all four stages (p<0.05). Moreover, a G/T mutation in exon 8 was identified and association analysis with meat quality traits showed that it was significantly associated with lean meat percentage (p<0.05). Our data may provide further insight into the molecular mechanisms responsible for breed-specific differences in porcine growth and meat quality.

Single nucleotide polymorphism association study for backfat and intramuscular fat content in the region between SW2098 and SW1881 on pig chromosome 6

This study was carried out to identify SNP associated with fatness traits on pig chromosome 6. In total, 11,067 putative genomic variations were detected in 125 complete bacterial artificial chromosome sequences corresponding to the region between SW2098 and SW1881, which harbors multiple QTL affecting intramuscular fat content (IMF) and backfat thickness (BFT). Among 173 putative SNP validated by MassArray, 120 SNP were used in an association study on 541 offspring produced by a cross of Korean native pig and Landrace breeds. The significance level of each SNP was determined using single marker regression analysis. Further, significant threshold values were determined using a false discovery rate. Nine out of 120 SNP showed significant effects on BFT or IMF or both. Of the 9 significant SNP, 4 were significantly associated with IMF, 7 were significantly related to BFT, and 2 SNP (Kps8172 and Kps6413) showed significant effects on both traits. Moreover, multiple regression analysis considering all significant SNP was used to correct spurious false positives due to linkage disequilibrium. Consequently, only 1 SNP (Kps6413) was significant for IMF, whereas 4 SNP including Kps6413 showed significant effects on BFT. The significant SNP had generally additive effects and on average explained 1.72% of the genetic variation for IMF and 3.92% for BFT, respectively. These markers can potentially be applied in pig breeding programs for improving IMF and BFT traits after validation in other populations.

Mapping quantitative trait loci for T lymphocyte subpopulations in peripheral blood in swine

Background

Increased disease resistance through improved general immune capacity would be beneficial for the welfare and productivity of farm animals. T lymphocyte subpopulations in peripheral blood play an important role in immune capacity and disease resistance in animals. However, very little research to date has focused on quantitative trait loci (QTL) for T lymphocyte subpopulations in peripheral blood in swine.

Results

In the study, experimental animals consist of 446 piglets from three different breed populations. To identify QTL for T lymphocyte subpopulations in peripheral blood in swine, the proportions of CD4+, CD8+, CD4+CD8+, CD4+CD8-, CD4-CD8+, and CD4-CD8- T cells and the ratio of CD4+:CD8+ T cells were measured for all individuals before and after challenge with modified live CSF (classical swine fever) vaccine. Based on the combined data of individuals from three breed populations, genome-wide scanning of QTL for these traits was performed based on a variance component model, and the genome wide significance level for declaring QTL was determined via permutation tests as well as FDR (false discovery rate) correction. A total of 27 QTL (two for CD4+CD8+, one for CD4+CD8-, three for CD4-CD8+, two for CD4-CD8-, nine for CD4+, two for CD8+, and eight for CD4+:CD8+ ratio) were identified with significance level of FDR < 0.10, of which 11 were significant at the level of FDR < 0.05, including the five significant at FDR < 0.01.

Conclusions

Within these QTL regions, a number of known genes having potential relationships with the studied traits may serve as candidate genes for these traits. Our findings herein are helpful for identification of the causal genes underlying these immune-related trait and selection for immune capacity of individuals in swine breeding in the future.

The pig genome project has plenty to squeal about

Significant progress on pig genetics and genomics research has been witnessed in recent years due to the integration of advanced molecular biology techniques, bioinformatics and computational biology, and the collaborative efforts of researchers in the swine genomics community. Progress on expanding the linkage map has slowed down, but the efforts have created a higher-resolution physical map integrating the clone map and BAC end sequence. The number of QTL mapped is still growing and most of the updated QTL mapping results are available through PigQTLdb. Additionally, expression studies using high-throughput microarrays and other gene expression techniques have made significant advancements. The number of identified non-coding RNAs is rapidly increasing and their exact regulatory functions are being explored. A publishable draft (build 10) of the swine genome sequence was available for the pig genomics community by the end of December 2010. Build 9 of the porcine genome is currently available with Ensembl annotation; manual annotation is ongoing. These drafts provide useful tools for such endeavors as comparative genomics and SNP scans for fine QTL mapping. A recent community-wide effort to create a 60K porcine SNP chip has greatly facilitated whole-genome association analyses, haplotype block construction and linkage disequilibrium mapping, which can contribute to whole-genome selection. The future 'systems biology' that integrates and optimizes the information from all research levels can enhance the pig community's understanding of the full complexity of the porcine genome. These recent technological advances and where they may lead are reviewed.

The mononuclear phagocyte system of the pig as a model for understanding human innate immunity and disease

The biology of cells of the mononuclear phagocyte system has been studied extensively in the mouse. Studies of the pig as an experimental model have commonly been consigned to specialist animal science journals. In this review, we consider some of the many ways in which the innate immune systems of humans differ from those of mice, the ways that pigs may address the shortcomings of mice as models for the study of macrophage differentiation and activation in vitro, and the biology of sepsis and other pathologies in the living animal. With the completion of the genome sequence and the characterization of many key regulators and markers, the pig has emerged as a tractable model of human innate immunity and disease that should address the limited, predictive value of rodents in preclinical studies.

Meta-analysis of results from quantitative trait loci mapping studies on pig chromosome 4

Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this study, we performed a meta-analysis of QTL on chromosome 4 in pig, using data from 25 separate experiments. First, a meta-analysis was performed for individual traits: average daily gain and backfat thickness. Second, a meta-analysis was performed for the QTL of three traits affecting loin yield: loin eye area, carcass length and loin meat weight. Third, 78 QTL were selected from 20 traits that could be assigned to one of three broad categories: carcass, fatness or growth traits. For each analysis, the number of identified meta-QTL was smaller than the number of initial QTL. The reduction in the number of QTL ranged from 71% to 86% compared to the total number before the meta-analysis. In addition, the meta-analysis reduced the QTL confidence intervals by as much as 85% compared to individual QTL estimates. The reduction in the confidence interval was greater when a large number of independent QTL was included in the meta-analysis. Meta-QTL related to growth and fatness were found in the same region as the FAT1 region. Results indicate that the meta-analysis is an efficient strategy to estimate the number and refine the positions of QTL when QTL estimates are available from multiple populations and experiments. This strategy can be used to better target further studies such as the selection of candidate genes related to trait variation.

Combining two Meishan F2 crosses improves the detection of QTL on pig chromosomes 2, 4 and 6

Background

In pig, a number of experiments have been set up to identify QTL and a multitude of chromosomal regions harbouring genes influencing traits of interest have been identified. However, the mapping resolution remains limited in most cases and the detected QTL are rather inaccurately located. Mapping accuracy can be improved by increasing the number of phenotyped and genotyped individuals and/or the number of informative markers. An alternative approach to overcome the limited power of individual studies is to combine data from two or more independent designs.

Methods

In the present study we report a combined analysis of two independent design (a French and a Dutch F2 experimental designs), with 2000 F2 individuals. The purpose was to further map QTL for growth and fatness on pig chromosomes 2, 4 and 6. Using QTL-map software, uni- and multiple-QTL detection analyses were applied separately on the two pedigrees and then on the combination of the two pedigrees.

Results

Joint analyses of the combined pedigree provided (1) greater significance of shared QTL, (2) exclusion of false suggestive QTL and (3) greater mapping precision for shared QTL.

Conclusions

Combining two Meishan x European breeds F2 pedigrees improved the mapping of QTL compared to analysing pedigrees separately. Our work was facilitated by the access to raw phenotypic data and DNA of animals from both pedigrees and the combination of the two designs with the addition of new markers allowed us to fine map QTL without phenotyping additional animals.

Joint QTL analysis of three connected F2-crosses in pigs

Background

Numerous QTL mapping resource populations are available in livestock species. Usually they are analysed separately, although the same founder breeds are often used. The aim of the present study was to show the strength of analysing F₂-crosses jointly in pig breeding when the founder breeds of several F₂-crosses are the same.

Methods

Three porcine F₂-crosses were generated from three founder breeds (i.e. Meishan, Pietrain and wild boar). The crosses were analysed jointly, using a flexible genetic model that estimated an additive QTL effect for each founder breed allele and a dominant QTL effect for each combination of alleles derived from different founder breeds. The following traits were analysed: daily gain, back fat and carcass weight. Substantial phenotypic variation was observed within and between crosses. Multiple QTL, multiple QTL alleles and imprinting effects were considered. The results were compared to those obtained when each cross was analysed separately.

Results

For daily gain, back fat and carcass weight, 13, 15 and 16 QTL were found, respectively. For back fat, daily gain and carcass weight, respectively three, four, and five loci showed significant imprinting effects. The number of QTL mapped was much higher than when each design was analysed individually. Additionally, the test statistic plot along the chromosomes was much sharper leading to smaller QTL confidence intervals. In many cases, three QTL alleles were observed.

Conclusions

The present study showed the strength of analysing three connected F₂-crosses jointly. In this experiment, statistical power was high because of the reduced number of estimated parameters and the large number of individuals. The applied model was flexible and was computationally fast.

Epistatic QTL pairs associated with meat quality and carcass composition traits in a porcine Duroc × Pietrain population

Background

Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.

Methods

Five hundred and eighty five F₂ pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F₂ animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.

Results

A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.

Conclusions

Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes.

Transcriptome analysis to identify differential gene expression affecting meat quality in heavy Italian pigs

Suppressive subtractive hybridization (SSH) was used to analyse the muscle transcriptome and identify genes affecting meat quality within an Italian pig population of Large White and Landrace purebred individuals. Seven phenotypes were recorded at slaughter: dorsal fat thickness, ham fat thickness, ham fat coverage, muscle compactness, marbling, meat colour and colour uniformity. Two subtractive libraries were created from longissimus dorsi tissue of selected pigs with extreme phenotypes for meat quality. Eighty-four differentially expressed ESTs were identified, which showed homology to expressed pig sequences and/or to genomic pig sequences produced within the pig genome project. Sixty-eight sequences were mapped on the pig genome, and most of these sequences co-localized with the same chromosomal positions as QTLs that have been previously identified for meat quality. Thirty sequences, including eight matching known genes previously related to muscle metabolic pathways, were selected to statistically validate their differential expression. Association analysis and t-test results indicated that 28 ESTs of the 30 analysed were associated with phenotypes investigated here and have significant differential expression levels (P≤ 0.05) between the two tails of the phenotypic distribution.

Combined line-cross and half-sib QTL analysis in Duroc-Pietrain population

A Duroc-Pietrain resource population was built to detect quantitative trait loci (QTL) that affect growth, carcass composition, and pork quality. The data were analyzed by applying three least-squares Mendelian models: a line-cross (LC) model, a half-sib (HS) model, and a combined LC and HS model (CB), which enabled the detection of QTL that had fixed, equal, and different allele frequencies for alternate breed alleles, respectively. Permutation tests were performed to determine 5% chromosome-wide and 5% genome-wide threshold values. A total of 40 (137) QTL were detected at the 5% genome-wide (chromosome-wide) level for the 35 traits analyzed. Of the 137 QTL detected, 62 were classified as the LC type (LC-QTL), 47 as the HS type (HS-QTL), and 28 as the CB type (CB-QTL). The results indicate that implementation of a series of model-based framework is not only beneficial to detect QTL, but also provides us with a new and more robust interpretation from which further methodology could be developed.

Quantitative trait loci for production traits in pigs: a combined analysis of two Meishan x Large White populations

Combined analysis of data from two or more resource populations can improve the power and accuracy of QTL mapping and allow some cross-validation of results. In this study, we performed a genome-wide scan using combined data from two F(2) populations derived from a cross between Large White and Chinese Meishan pigs. A total of 739 pigs were included in the analysis. In total 187 markers were genotyped in the two populations, including 115 markers genotyped in both populations, and these markers covered 2282 cM of the pig genome with an average of 13.58 cM between markers. Seven traits (teat number, birth weight, weaning weight, test-end weight, fat depth at shoulder, fat depth at mid back and fat depth at loin) were analysed for both individual populations and the combined population. There were 9 (2, 10), 1 (4, 4) and 14 (5, 18) QTL that achieved 1% genome-wide, 5% genome-wide and suggestive significance levels respectively in population 1 (population 2, combined population). Additive effects of QTL detected in the two populations at all significance levels were largely consistent suggesting that the QTL represent real genetic effects, but this was not the case for dominance or imprinting effects. There were also a number of significant interactions between detected QTL effects and population.

Large-scale, multibreed, multitrait analyses of quantitative trait loci experiments: the case of porcine X chromosome

A QTL analysis of multibreed experiments (i.e., crossed populations involving more than two founder breeds) offers clear advantages over classical two-breed crosses, among them increased power and a more comprehensive coverage of the total genetic variability in the species. An alternative to designed multibreed crosses is to reanalyze jointly several experiments involving different breeds. We report a multibreed, multitrait QTL analysis of SSCX that involves five different crosses, six breeds, and almost 3,000 genotyped individuals using a truly multibreed strategy to allow for any number of founder breed origins. Traits analyzed were growth, fat thickness, carcass length, and shoulder and ham weights. Generally, the joint analysis resulted in more significant QTL than the single-experiment analyses. We show that the QTL for fatness, which is highly significant (nominal P < 10(-43)), is of Asiatic origin (Meishan). The next most significant QTL (nominal P < 10(-15)) affected ham weight and seems to be segregating only between Large White and the rest of the breeds. A multitrait, multi-QTL analysis suggests that these are two distinct loci. Additionally, a locus segregating only between Iberian and Landrace affects live weight. The advantages of joint, multibreed analyses clearly outweigh their potential risks.

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

White meat is the most economically valuable part of a broiler chicken. Increasing white meat relative to overall body size (white meat percentage, WM%) makes a broiler, gram for gram, a more valuable animal. However, accurately measuring WM% requires removing the bird from the breeding flock. Identification of markers for genomic regions associated with WM% would allow direct genetic selection on breeders. The objective of the current study was to identify genomic regions affecting WM% and other growth and carcass traits in an F2 cross between 2 commercial broiler lines that differed in WM%. Two commercial lines were crossed to generate 5 F1 half-sib families of each reciprocal cross type. One male from each family was crossed with 3 females from each of the other families within each reciprocal cross type. Seven F2 half-sib families, totaling 430 F2 individuals, were analyzed. Microsatellite markers (n = 73) on the 11 largest chromosomes were analyzed for associations with various growth and carcass traits by least squares interval mapping using line-cross, half-sib, combined, and parent of origin models. Sixty-eight QTL were identified at the 5% chromosome-wise level, including 6 QTL affecting WM%. Ten QTL reached 5% genome-wise significance, including 1 WM% QTL on Gga 2. The current study identified genomic regions harboring QTL affecting WM% and other carcass and growth traits, which may be useful for direct genetic selection, and also identified putative imprinted QTL in the chicken. The advantage of using multiple statistical models was evident because QTL were identified with the combined and parent of origin models that were not identified with the line-cross or half-sib models.