Genes for Skeletal Strength in Poultry

A unique resource population was used to determine that variation in a gene of the bone morphogenetic protein (BMP) family is associated with shank measurements in poultry. Knowledge of genetic variation and associations with traits related to skeletal integrity will enable genetic selection of poultry populations for stronger bones, thus reducing bone breakage in the live animal and on the processing line

Association of Liver X Receptor Alpha and Beta Genes with Carcass Lean and Fat Content in Pigs

A three-generation resource family of a cross between the Berkshire and Yorkshire (BY) pig breeds and four pig commercial populations were used to investigate whether the Liver X Receptor Alpha (LXRA) and Beta (LXRB) genes play a role in influencing lean and fat growth in pigs. Our current findings from this study have suggested that LXRA and LXRB might have potential effects, especially for loin lean and fat content

Chicken Quantitative Trait lLoci for Growth and Body Composition Associated with the Very Low Density Apolipoprotein-II Gene

Very low density apolipoprotein-II (apoVLDL-II) is a major constituent of very low density lipoprotein and is involved in lipid transportation in chickens. The current study was designed to investigate the associations of an apoVLDL-II gene polymorphism on chicken growth and body composition traits. The Iowa Growth and Composition Resource Population was established by crossing broiler sires with dams from 2 unrelated highly inbred lines (Leghorn and Fayoumi). The F1 birds were intercrossed, within dam line, to produce 2 related F2 populations. Body weight and body composition traits were measured in the F2 population. Primers for the 5\u27-flanking region in apoVLDL-II were designed from database chicken genomic sequence. Single nucleotide polymorphisms (SNP) between parental lines were detected by DNA sequencing, and PCR-RFLP methods were then developed to genotype SNP in the F2 population. There was no polymorphism in the 492 bp sequenced between broiler and Leghorn. The apoVLDL-II polymorphism between broiler and Fayoumi was associated with multiple traits of growth and body composition in the 148 male F2 individuals, including BW, breast muscle weight, drumstick weight, and tibia length. This research suggests that apoVLDL-II or a tightly linked gene has broad effects on growth and development in the chicken

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

Two informative chicken F2 populations based on crosses between a broiler breeder male line and dams from genetically distinct, highly inbred (\u3e99%) 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

Chicken Quantitative Trait Loci for Growth and Body Composition Associated with Transforming Growth Factor-β Genes1

Transforming growth factor-β (TGF-β) belongs to a large family of multifunctional growth factors that regulate a broad spectrum of biological activities involved in morphogenesis, development, and differentiation. The current study was designed to investigate the effects of TGF-β genes on chicken growth and body composition traits. The Iowa Growth and Composition Resource Population was established by crossing broiler sires with dams from two unrelated highly inbred lines (Leghorn and Fayoumi). The F1 birds were intercrossed, within dam line, to produce two related F2 populations. Body weight and body composition traits were measured in the F 2 population. Primers for TGF-β2, TGF-β3, and TGF-β4 were designed from database chicken sequence. Polymorphisms between parental lines were detected by DNA sequencing, and PCR-RFLP methods were then developed to screen the F2 population. The TGF-β2 polymorphisms between broiler and Leghorn and the TGF-β4 polymorphism between broiler and Fayoumi were associated with traits of skeletal integrity, such as tibia length, bone mineral content, bone mineral density, and the percentage of each measure to BW. The TGF-β3 polymorphism between broilers and Leghorns was associated with traits of growth and body composition, such as BW, average daily gain, weight of breast muscle, abdominal fat pad and spleen, as well as the percentage of these organ weights to BW, and the percentage of shank weight and length to BW. The current research supports the broad effects of TGF-β genes on growth and development of chickens

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

Two unique chicken F2 populations generated from a broiler breeder male line and 2 genetically distinct inbred (\u3e99%) 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 F2 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

Identification of low-confidence regions in the pig reference genome (Sscrofa10.2)

Many applications of high throughput sequencing rely on the availability of an accurate reference genome. Variant calling often produces large data sets that cannot be realistically validated and which may contain large numbers of false-positives. Errors in the reference assembly increase the number of false-positives. While resources are available to aid in the filtering of variants from human data, for other species these do not yet exist and strict filtering techniques must be employed which are more likely to exclude true-positives. This work assesses the accuracy of the pig reference genome (Sscrofa10.2) using whole genome sequencing reads from the Duroc sow whose genome the assembly was based on. Indicators of structural variation including high regional coverage, unexpected insert sizes, improper pairing and homozygous variants were used to identify low quality (LQ) regions of the assembly. Low coverage (LC) regions were also identified and analyzed separately. The LQ regions covered 13.85% of the genome, the LC regions covered 26.6% of the genome and combined (LQLC) they covered 33.07% of the genome. Over half of dbSNP variants were located in the LQLC regions. Of CNVRs identified in a previous study, 86.3% were located in the LQLC regions. The regions were also enriched for gene predictions from RNA-seq data with 42.98% falling in the LQLC regions. Excluding variants in the LQ, LC or LQLC from future analyses will help reduce the number of false-positive variant calls. Researchers using WGS data should be aware that the current pig reference genome does not give an accurate representation of the copy number of alleles in the original Duroc sow’s genome

Design and development of exome capture sequencing for the domestic pig (Sus scrofa)

Background: The domestic pig (Sus scrofa) is both an important livestock species and a model for biomedical research. Exome sequencing has accelerated identification of protein-coding variants underlying phenotypic traits in human and mouse. We aimed to develop and validate a similar resource for the pig.Results: We developed probe sets to capture pig exonic sequences based upon the current Ensembl pig gene annotation supplemented with mapped expressed sequence tags (ESTs) and demonstrated proof-of-principle capture and sequencing of the pig exome in 96 pigs, encompassing 24 capture experiments. For most of the samples at least 10x sequence coverage was achieved for more than 90% of the target bases. Bioinformatic analysis of the data revealed over 236,000 high confidence predicted SNPs and over 28,000 predicted indels.Conclusions: We have achieved coverage statistics similar to those seen with commercially available human and mouse exome kits. Exome capture in pigs provides a tool to identify coding region variation associated with production traits, including loss of function mutations which may explain embryonic and neonatal losses, and to improve genomic assemblies in the vicinity of protein coding genes in the pig