Genome‐wide association study for egg production and quality in layer chickens

Discovery of genes with large effects on economically important traits has for many years been of interest to breeders. The development of SNP panels which cover the whole genome with high density and, more importantly, that can be genotyped on large numbers of individuals at relatively low cost, has opened new opportunities for genome‐wide association studies (GWAS). The objective of this study was to find genomic regions associated with egg production and quality traits in layers using analysis methods developed for the purpose of whole genome prediction. Genotypes on over 4500 birds and phenotypes on over 13 000 hens from eight generations of a brown egg layer line were used. Birds were genotyped with a custom 42K Illumina SNP chip. Recorded traits included two egg production and 11 egg quality traits (puncture score, albumen height, yolk weight and shell colour) at early and late stages of production, as well as body weight and age at first egg. Egg weight was previously analysed by Wolc et al. ( 2012 ). The Bayesian whole genome prediction model – BayesB (Meuwissen et al. 2001 ) was used to locate 1 Mb regions that were most strongly associated with each trait. The posterior probability of a 1 Mb window contributing to genetic variation was used as the criterion for suggesting the presence of a quantitative trait locus (QTL) in that window. Depending upon the trait, from 1 to 7 significant (posterior probability >0.9) 1 Mb regions were found. The largest QTL, a region explaining 32% of genetic variance, was found on chr4 at 78 Mb for body weight but had pleiotropic effects on other traits. For the other traits, the largest effects were much smaller, explaining <7% of genetic variance, with regions on chromosomes 2, 12 and 17 explaining above 5% of genetic variance for albumen height, shell colour and egg production, respectively. In total, 45 of 1043 1 Mb windows were estimated to have a non‐zero effect with posterior probability > 0.9 for one or more traits.     

Modelling cumulative egg production in laying hens and parent stocks of broiler chickens using classical growth functions

ABSTRACT

1. The objective of the present study is to introduce fresh insight into modelling of egg production by applying classical growth functions to egg production records reported by Aviagen Management Guide to laying hens and the parent stock of broiler chickens.

2. The functions (monomolecular, logistic, Gompertz, Richards and Morgan) were fitted using nonlinear regression procedures of SAS software, and their performance was assessed using goodness-of-fit statistics (coefficient of determination, residual mean squares, Akaike information criterion and Bayesian information criterion).

3. Overall, except for the logistic and Gompertz, the growth functions evaluated gave an acceptable fit to the cumulative egg production curves, with the Morgan equation ranking first followed by the Richards equation. The Morgan and Richards equations provided satisfactory predictions of weekly egg yield at different egg production stages, from early to late production, whereas the least accurate estimates were obtained with the logistic equation.

4. In conclusion, classical growth functions proved feasible alternatives to fit cumulative egg production curves of laying hens and parent stock of broiler chickens, resulting in suitable statistical performance and accurate estimates of production.     

Practical capability of a DNA pool‐based genome‐wide association study using BovineSNP50 array in a cattle population

Genome‐wide association mapping for complex traits in cattle populations is a powerful, but expensive, selection tool. The DNA pooling technique can potentially reduce the cost of genome‐wide association studies. However, in DNA pooling design, the additional variance generated by pooling‐specific errors must be taken into account. Therefore, this study aimed to investigate factors such as: (i) the accuracy of allele frequency estimation; (ii) the magnitude of errors in pooling construction and in the array; and (iii) the effect of the number of replicate arrays on P‐values estimated by a genome‐wide association study. Results showed that the Illumina correction method is the most effective method to correct the allele frequency estimation; pooling errors, especially array variance, should be taken into account in DNA pooling design; and the risk of a type I error can be reduced by using at least two replicate arrays. These results indicate the practical capability and cost‐effectiveness of pool‐based genome‐wide association studies using the BovineSNP50 array in a cattle population.     

A genome‐wide association study for canine cryptorchidism in Siberian Huskies

Cryptorchidism is a condition whereby one or both testes fail to descend into the scrotal sac. Here, we performed a genome‐wide association study (GWAS) with both a case–control analysis using the GEMMA software accounting for population structure and a BayesB approach in the GenSel software applied to every 1 Mb window of SNPs or haplotypes. The haplotypes were constructed from a genealogical tree using the population of 204 Siberian Huskies. The BayesB analyses identified six putative genomic candidate regions on CFA6, 9, 24, 27 and X. These regions explained a high percentage of genetic variance when compared with other genomic regions. The positional candidate genes Q9TSI5_CANFA (matrix metalloproteinase 9 precursor) on CFA24, ADAMTS20 (ADAM metallopeptidase with thrombospondin type 1 motif, 20) on CFA27 and MID1IP1 (MID1 interacting protein 1) on CFAX are known to be functionally related to extracellular matrix remodelling, which might be important for gubernaculum elongation and thus interrupting normal testicular descent. Further mutation screening in these candidate regions on CFA6, 9, 24, 27 and X is needed. Next generation sequencing will help to uncover rare variants associated with cryptorchidism in this dog population.     

全基因组关联分析在德国牧羊犬髋关节发育不良研究中的应用现状

犬髋关节发育不良(canine hip dysplasia,CHD)是犬常见的骨科疾病,传统放射学诊断对降低CHD发病率的作用有限,而基因诊断技术则可以有效促进CHD的育种改良。全基因组关联分析(genome wide association study,GWAS)是一种全基因组范围内的遗传标记的检测技术,对复杂性状功能基因的鉴定十分有效,已成为挖掘畜禽复杂疾病和性状遗传的重要方法。随着犬全基因组测序的完成以及犬不同密度SNP芯片的商业化,GWAS已经成为CHD致病基因筛选的一个重要手段。本文综述了GWAS的定义与影响因素,CHD在国外的育种现状及GWAS在德国牧羊犬中的研究进展。     

Progress of genome wide association study in domestic animals

ABSTRACT: Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described.     

A genome‐wide association study for fat‐related traits computed by image analysis in Japanese Black cattle

The objective of this study was to identify genomic regions associated with fat‐related traits using a Japanese Black cattle population in Hyogo. From 1836 animals, those with high or low values were selected on the basis of corrected phenotype and then pooled into high and low groups (n = 100 each), respectively. DNA pool‐based genome‐wide association study (GWAS) was performed using Illumina BovineSNP50 BeadChip v2 with three replicate assays for each pooled sample. GWAS detected that two single nucleotide polymorphisms (SNPs) on BTA7 (ARS‐BFGL‐NGS‐35463 and Hapmap23838‐BTA‐163815) and one SNP on BTA12 (ARS‐BFGL‐NGS‐2915) significantly affected fat percentage (FAR). The significance of ARS‐BFGL‐NGS‐35463 on BTA7 was confirmed by individual genotyping in all pooled samples. Moreover, association analysis between SNP and FAR in 803 Japanese Black cattle revealed a significant effect of SNP on FAR. Thus, further investigation of these regions is required to identify FAR‐associated genes and mutations, which can lead to the development of DNA markers for marker‐assisted selection for the genetic improvement of beef quality.     

Power of a genome scan to detect and locate quantitative trait loci in cattle using dense single nucleotide polymorphisms

There is increasing use of dense single nucleotide polymorphisms (SNPs) for whole‐genome association studies (WGAS) in livestock to map and identify quantitative trait loci (QTL). These studies rely on linkage disequilibrium (LD) to detect an association between SNP genotypes and phenotypes. The power and precision of these WGAS are unknown, and will depend on the extent of LD in the experimental population. One complication for WGAS in livestock populations is that they typically consist of many paternal half‐sib families, and in some cases full‐sib families; unless this subtle population stratification is accounted for, many spurious associations may be reported. Our aim was to investigate the power, precision and false discovery rates of WGAS for QTL discovery, with a commercial SNP array, given existing patterns of LD in cattle. We also tested the efficiency of selective genotyping animals. A total of 365 cattle were genotyped for 9232 SNPs. We simulated a QTL effect as well as polygenic and environmental effects for all animals. One QTL was simulated on a randomly chosen SNP and accounted for 5%, 10% or 18% of the total variance. The power to detect a moderate‐sized additive QTL (5% of the phenotypic variance) with 365 animals genotyped was 37% (p < 0.001). Most importantly, if pedigree structure was not accounted for, the number of false positives significantly increased above those expected by chance alone. Selective genotyping also resulted in a significant increase in false positives, even when pedigree structure was accounted for.     

Identification of candidate genes for blood metabolites in Iranian chickens using a genome-wide association study

1. In order to identify loci associated with metabolic traits, a genome-wide association study was carried out in a chicken F2 population derived from a reciprocal cross between Iranian Urmia indigenous chickens and Arian broiler line using Illumina 60K Chicken single nucleotide polymorphism (SNP) BeadChip.

2. Six traits including plasma level of triglycerides (TGs), cholesterol (Chol), glucose (Glu), total protein, albumin (Alb) and globulin (Glo) were recorded. The association between the identified SNPs and metabolic traits was estimated by general linear model (GLM) and compressed mixed linear model (CMLM).

3. A total of 38 SNPs were identified at the genome-wide significant and suggestive levels, of which 5 SNPs reached a 5% Bonferroni genome-wide significance (P < 2.58E-6) for TG, Alb and Glo through CMLM, and 21 SNPs were significantly associated with TG, Chol, Glu, Alb and Glo through GLM.

4. Gene ontology showed that these SNPs were located within or near the candidate genes responsible for metabolic traits.

5. In conclusion, the identified candidate genes provided novel information for molecular mechanisms underlying metabolic traits. These findings are important in marker-assisted selection in the chicken breeding scheme.     

Genome‐wide association study for feedlot average daily gain in Nellore cattle (Bos indicus)

The genome‐wide association study (GWAS) results are presented for average daily gain (ADG) in Nellore cattle. Phenotype of 720 male Bos indicus animals with information of ADG in feedlots and 354 147 single‐nucleotide polymorphisms (SNPs) obtained from a database added by information from Illumina Bovine HD (777 962 SNPs) and Illumina BovineSNP50 (54 609) by imputation were used. After quality control and imputation, 290 620 SNPs remained in the association analysis, using R package Genome‐wide Rapid Association using Mixed Model and Regression method GRAMMAR‐Gamma. A genomic region with six significant SNPs, at Bonferroni‐corrected significance, was found on chromosome 3. The most significant SNP (rs42518459, BTA3: 85849977, p = 9.49 × 10^?8) explained 5.62% of the phenotypic variance and had the allele substitution effect of ?0.269 kg/day. Important genes such as PDE4B, LEPR, CYP2J2 and FGGY are located near this region, which is overlapped by 12 quantitative trait locus (QTLs) described for several production traits. Other regions with markers with suggestive effects were identified in BTA6 and BTA10. This study showed regions with major effects on ADG in Bos indicus in feedlots. This information may be useful to increase the efficiency of selecting this trait and to understand the physiological processes involved in its regulation.     

Genome‐wide association study of cell‐mediated immune response in chicken

Cell‐mediated immunity (CMI) causes the intracellular destruction of the antigen or elimination of the host cell to make animals resistant against exogenous antigens and cancers. In this study, a genome‐wide association study (GWAS) was carried out to identify genomic regions associated with CMI in chicken using chicken 60k high‐density single nucleotide polymorphism (SNP) array. Genomic relationships were taken into account to adjust for population structure. In order to account for multiple testing, chromosome‐wise false discovery rate was controlled at 5% and 10% levels. Moreover, a comparison of the power of fixed and mixed linear models based on genomic inflation factor was carried out. Mixed linear model (MLM) had better inflation rate, and therefore the results from MLM were used for subsequent analysis. Three significantly associated SNPs (FDR < 0.05) on chromosome 24 and linkage group E22C19W28_E50C23, and three suggestively associated SNPs (FDR < 0.1) on chromosome 1, 5 and 16 were identified. Pathway analysis showed that two biological pathways, which are related to immune response, were strongly associated with the candidate genes surrounding identified SNPs, and their influences were mostly on antigen processing and presentation, and cellular structure.     

A genomewide association mapping study using ultrasound‐scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle

The aim of this study was to identify candidate genes and genomic regions associated with ultrasound‐derived measurements of the rib‐eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.