Evaluation of a multi-line broiler chicken population using a single-step genomic evaluation procedure

Effects on prediction of analysing a multi-line chicken population as one line were evaluated. Body weight records were provided by Cobb-Vantress for two lines of broiler chickens. Phenotypic records for 183 695 and 164 149 broilers and genotypic records for 3195 and 3001 broilers were available for each line. Lines were combined to create a multi-line population and analysed using a single-step procedure combining the additive relationship matrix and the genomic relationship matrix (G). G was scaled using allele frequencies from each line, the multi-line population, or 0.5. When allele frequencies were calculated from each line, distributions of diagonal elements were bimodal. When allele frequencies were calculated from the multi-line population, the distribution of diagonal elements had one peak. When allele frequency 0.5 was used, the distribution was bimodal. Genomic estimated breeding values (GEBVs) were predicted using each allele frequency. GEBVs differed with allele frequency but had ≥ 0.99 correlations with GEBVs predicted with correct allele frequencies. Means of each line and differences in mean between the lines differed based on allele frequencies. Assumed allele frequencies have little impact on ranking within line but larger impact on ranking across lines. G may be used to evaluate multiple populations simultaneously but must be adjusted to obtain properly scaled estimates when population structure is unknown.     

Different methods of selecting animals for genotyping to maximize the amount of genetic information known in the population

It is possible to predict genotypes of some individuals based on genotypes of relatives. Different methods of sampling individuals to be genotyped from populations were evaluated using simulation. Simulated pedigrees included 5,000 animals and were assigned genotypes based on assumed allelic frequencies for a SNP (favorable/unfavorable) of 0.3/0.7, 0.5/0.5, and 0.8/0.2. A field data pedigree (29,101 animals) and a research pedigree (8,688 animals) were used to test selected methods using simulated genotypes with allelic frequencies of 0.3/0.7 and 0.5/0.5. For the simulated pedigrees, known and unknown allelic frequencies were assumed. The methods used included random sampling, selection of males, and selection of both sexes based on the diagonal element of the inverse of the relationship matrix (A(-1)) and absorption of either the A or A(-1) matrix. For random sampling, scenarios included selection of 5 and 15% of the animals, and all other methods presented concentrated on the selection of 5% of the animals for genotyping. The methods were evaluated based on the percentage of alleles correctly assigned after peeling (AK(P)), the probability of assigning true alleles (AK(G)), and the average probability of correctly assigning the true genotype. As expected, random sampling was the least desirable method. The most desirable method in the simulated pedigrees was selecting both males and females based on their diagonal element of A(-1). Increases in AK(P) and AK(G) ranged from 26.58 to 29.11% and 2.76 to 6.08%, respectively, when males and females (equal to 5% of all animals) were selected based on their diagonal element of A(-1) compared with selecting 15% of the animals at random. In the case of a real beef cattle pedigree, selection of males only or males and females yielded similar results and both selection methods were superior to random selection.     

Genotype distribution and allele frequencies of the genes associated with body composition and locomotion traits in Myanmar native horses

Myanmar native horses are small horses used mainly for drafting carts or carriages in rural areas and packing loads in mountainy areas. In the present study, we investigated genotype distributions and allele frequencies of the LCORL/NCAPG, MSTN and DMRT3 genes, which are associated with body composition and locomotion traits of horses, in seven local populations of Myanmar native horses. The genotyping result of LCORL/NCAPG showed that allele frequencies of C allele associated with higher withers height ranged from 0.08 to 0.27, and 0.13 in average. For MSTN, allele frequencies of C allele associated with higher proportion of Type 2B muscular fiber ranged from 0.05 to 0.23, and 0.09 in average. For DMRT3, allele frequencies of A allele associated with ambling gait ranged from 0 to 0.04, and 0.01 in average. The presences of the minor alleles of these genes at low frequencies suggest a possibility that these horse populations have not been under strong selection pressure for particular locomotion traits and body composition. Our findings of the presence of these minor alleles in Southeast Asian native horses are also informative for considering the origins of these minor alleles associated with body composition and locomotion traits in horse populations.     

Implications of SNP weighting on single‐step genomic predictions for different reference population sizes

We investigated the importance of SNP weighting in populations with 2,000 to 25,000 genotyped animals. Populations were simulated with two effective sizes (20 or 100) and three numbers of QTL (10, 50 or 500). Pedigree information was available for six generations; phenotypes were recorded for the four middle generations. Animals from the last three generations were genotyped for 45,000 SNP. Single‐step genomic BLUP (ssGBLUP) and weighted ssGBLUP (WssGBLUP) were used to estimate genomic EBV using a genomic relationship matrix ( G ). The WssGBLUP performed better in small genotyped populations; however, any advantage for WssGBLUP was reduced or eliminated when more animals were genotyped. WssGBLUP had greater resolution for genome‐wide association (GWA) as did increasing the number of genotyped animals. For few QTL, accuracy was greater for WssGBLUP than ssGBLUP; however, for many QTL, accuracy was the same for both methods. The largest genotyped set was used to assess the dimensionality of genomic information (number of effective SNP). The number of effective SNP was considerably less in weighted G than in unweighted G . Once the number of independent SNP is well represented in the genotyped population, the impact of SNP weighting becomes less important.     

Effect of different genomic relationship matrices on accuracy and scale

Phenotypic data on BW and breast meat area were available on up to 287,614 broilers. A total of 4,113 birds were genotyped for 57,636 SNP. Data were analyzed by a single-step genomic BLUP (ssGBLUP), which accounts for all phenotypic, pedigree, and genomic information. The genomic relationship matrix (G) in ssGBLUP was constructed using either equal (0.5; GEq) or current (GC) allele frequencies, and with all SNP or with SNP with minor allele frequencies (MAF) below multiple thresholds (0.1, 0.2, 0.3, and 0.4) ignored. Additionally, a pedigree-based relationship matrix for genotyped birds (A(22)) was available. The matrices and their inverses were compared with regard to average diagonal (AvgD) and off-diagonal (AvgOff) elements. In A(22), AvgD was 1.004 and AvgOff was 0.014. In GEq, both averages decreased with the increasing thresholds for MAF, with AvgD decreasing from 1.373 to 1.020 and AvgOff decreasing from 0.722 to 0.025. In GC, AvgD was approximately 1.01 and AvgOff was 0 for all MAF. For inverses of the relationship matrices, all AvgOff were close to 0; AvgD was 2.375 in A(22), varied from 11.563 to 12.943 for GEq, and increased from 8.675 to 12.859 for GC as the threshold for MAF increased. Predictive ability with all GEq and GC was similar except that at MAF = 0.4, they declined by 0.01 for BW and improved by 0.01 for breast meat area. Compared with BLUP, EBV in the ssGBLUP were, on average, increased by up to 1 additive SD greater with GEq and decreased by 2 additive SD less with GC. Genotyped animals were biased upward with GEq and downward with GC. The biases and differences in EBV could be controlled by adding a constant to GC; they were eliminated with a constant of 0.014, which corresponds to AvgOff in A(22). Unbiased evaluation in the ssGBLUP may be obtained with GC scaled to be compatible with A(22). The reduction of SNP with small MAF has a small effect on the real accuracy, but it may falsely increase the estimated accuracies by inversion.     

Genetic characterization of Barbari goats using microsatellite markers

Genetic variation in Barbari goats, a highly prolific breed distributed widely in the northern part of India, known for better milk and meat quality, was studied as a part of genetic characterization and conservation. The genomic DNA from 50 unrelated Barbari goats were amplified via PCR with a panel of 21 microsatellite markers, and resolved through 6 per cent denaturing polyacrylamide gel electrophoresis followed by silver staining. The number of alleles ranged from 4 to 11, with allele sizes ranging from 88 to 220 bp. The distribution of allele frequencies was between 0.0104 and 0.5208. Polymorphism information content varied from 0.5563 to 0.8348. The population was not in Hardy-Weinberg equilibrium for all except two microsatellite loci (ILSTS044 and ILSTS060). The observed heterozygosity ranged from 0.8478 to 1.0000 while the expected heterozygosity ranged from 0.6208 to 0.8509. Based on the results of the present study, there is a good scope for exploiting the genetic variability in the Barbari goats for further improvement of performance.     

Effect of marker‐data editing on the accuracy of genomic prediction

Genomic selection is a method to predict breeding values using genome‐wide single‐nucleotide polymorphism (SNP) markers. High‐quality marker data are necessary for genomic selection. The aim of this study was to investigate the effect of marker‐editing criteria on the accuracy of genomic predictions in the Nordic Holstein and Jersey populations. Data included 4429 Holstein and 1071 Jersey bulls. In total, 48 222 SNP for Holstein and 44 305 SNP for Jersey were polymorphic. The SNP data were edited based on (i) minor allele frequencies (MAF) with thresholds of no limit, 0.001, 0.01, 0.02, 0.05 and 0.10, (ii) deviations from Hardy–Weinberg proportions (HWP) with thresholds of no limit, chi‐squared p‐values of 0.001, 0.02, 0.05 and 0.10, and (iii) GenCall (GC) scores with thresholds of 0.15, 0.55, 0.60, 0.65 and 0.70. The marker data sets edited with different criteria were used for genomic prediction of protein yield, fertility and mastitis using a Bayesian variable selection and a GBLUP model. De‐regressed EBV were used as response variables. The result showed little difference between prediction accuracies based on marker data sets edited with MAF and deviation from HWP. However, accuracy decreased with more stringent thresholds of GC score. According to the results of this study, it would be appropriate to edit data with restriction of MAF being between 0.01 and 0.02, a p‐value of deviation from HWP being 0.05, and keeping all individual SNP genotypes having a GC score over 0.15.     

Marker-based estimates of between and within population kinships for the conservation of genetic diversity

In this article coefficients of kinship between and within populations are proposed as a tool to assess genetic diversity for conservation of genetic variation. However, pedigree-based kinships are often not available, especially between populations. A method of estimation of kinship from genetic marker data was applied to simulated data from random breeding populations in order to study the suitability of this method for livestock conservation plans. Average coefficients of kinship between populations can be estimated with low Mean Square Error of Prediction, although a bias will occur from alleles that are alike in state in the founder population. The bias is similar for all populations, so the ranking of populations will not be affected. Possible ways of diminishing this bias are discussed. The estimation of kinships between individuals is imprecise unless the number of marker loci is large (> 200). However, it allows distinction between highly related animals (full sibs, half sibs and equivalent relations) and animals that are not directly related if about 30–50 polymorphic marker genes are used. The marker-based estimates of kinship coefficients yielded higher correlations than genetic distance measures with pedigree-based kinships and thus to this measure of genetic diversity, although correlations were high overall. The relation between coefficients of kinship and genetic distances are discussed. Kinship-based diversity measures conserve the founder population allele frequencies, whereas genetic distances will conserve populations in which allele frequencies are the most different. Marker-based kinship estimates can be used for the selection of breeds and individuals as contributors to a genetic conservation programme.     

Identification of the putative ancestral allele of bovine single‐nucleotide polymorphisms

Identifying the action of natural selection from patterns of standing genetic variation has long been of interest to the population genetic community. Thanks to the availability of large single‐nucleotide polymorphism (SNP) data sets for many species and of high‐throughput SNP genotyping methods, whole‐genomic surveys to detect selective sweeps are now possible. Knowing the ancestral allele increases the power to detect selection. We present here a comparative genomic approach to determine the putative ancestral allele of bovine SNPs deposited in public databases. We analysed 19 551 488 SNPs and identified the putative ancestral allele for 14 339 107 SNPs. Our predicted ancestral alleles were in agreement with ancestral alleles detected by genotyping outgroup species for 97% SNPs from the BovineSNP50 BeadChip. This comparison indicates that our comparative genomic‐based approach to identify putative ancestral alleles is reliable.     

Genotypes and allele frequencies of buried SNPs in a bovine single‐nucleotide polymorphism array in Japanese Black cattle

Single nucleotide polymorphism (SNP) arrays are widely used for genetic and genomic analyses in cattle breeding; thus, data derived from SNP arrays have accumulated on a large scale nationwide. Commercial SNP arrays contain a considerable number of unassigned SNPs on the chromosome/position on the genome; these SNPs are excluded in subsequent analyses. Notably, the position‐unassigned SNPs, or “buried SNPs” include some of the markers associated with genetic disease. In this study, we identified the position of buried SNPs using the Basic Local Alignment Search Tool against the surrounding sequences and characterized the relationship between SNPs and genetic diseases in Online Mendelian Inheritance in Animals based on the genomic position. We determined the position of 285 buried SNPs on the genome and surveyed the genotype and allele frequencies of these SNPs in 5,955 individual Japanese Black cattle. Eleven SNPs associated with genetic disease, which contained five buried SNPs, were found in the population with the risk allele frequency ranging from 0.00008396 to 0.46. These results indicate that buried SNPs in the bovine SNP array can be utilized to identify associations with genetic disorders from large scale accumulated SNP genotype data in Japanese Black cattle.     

Mx基因抗性位点在11个不同鸡种中的分布及遗传结构分析

通过错配PCR技术检测Mx基因S631N位点的抗性等位基因A和敏感性等位基因G在11个不同鸡种中的分布差异。结果显示,错配PCR-RFLP能准确检测出抗性等位基因A与敏感性等位基因G在不同鸡种内的突变,抗性等位基因A在所有群体内的基因频率平均为0.502,敏感性等位基因G的频率平均为0.498;11个不同鸡种群体Mx基因S631N位点的观察杂合度平均为0.506 7,Shannon信息指数平均为0.562 9。在该位点上,11个鸡种,漳州斗鸡、吐鲁番斗鸡、皖南鸡、文昌鸡、如皋鸡、安卡鸡偏离了Hardy-Weinberg平衡(P<0.05)外,其余5个群体均处Hardy-Weinberg平衡状态(P>0.05);经Ewens-Watterson中立性检验,该位点在各群体内(除如皋鸡群体外)均属于中立性选择。基于该位点等位基因频率构建的UPGMA聚类图将11个不同鸡种分为3大类,聚类结果反映了11个不同鸡种在Mx基因抗性方面存在的差异和优势。     

微卫星分子标记分析四川绵羊群体遗传多样性

为探究四川省6个绵羊群体的遗传多样性,实验应用12个微卫星标记计算基因频率、有效等位基因数、杂合度及多态信息含量来评估群体内遗传多样度,通过遗传距离聚类图、群体结构推测图、主成分分析及群体间分子方差分析来评估群体间遗传关系。结果表明:6个绵羊群体在12个微卫星位点的平均有效等位基因数为3.006~3.176,平均多态信息含量变化为0.559~0.612,平均期望遗传杂合度为0.610~0.670;6个绵羊群体间的遗传关系与地理分布情况及育成史实不完全一致,但遗传距离聚类图、群体结构推测图和主成分分析结果均显示,6个绵羊群体中布拖黑绵羊类群与贾洛绵羊类群遗传关系更近;6个绵羊群体间方差组分F统计量结果为0.112 39,处于中度分化水平。     

Accuracy of imputation of single nucleotide polymorphism marker genotypes from low‐density panels in Japanese Black cattle

Using target and reference fattened steer populations, the performance of genotype imputation using lower‐density marker panels in Japanese Black cattle was evaluated. Population imputation was performed using BEAGLE software. Genotype information for approximately 40 000 single nucleotide polymorphism (SNP) markers by Illumina BovineSNP50 BeadChip was available, and imputation accuracy was assessed based on the average concordance rates of the genotypes, varying equally spaced SNP densities, and the number of individuals in the reference population. Two additional statistics were also calculated as indicators of imputation performance. The concordance rates tended to be lower for SNPs with greater minor allele frequencies, or those located near the ends of the chromosomes. Longer autosomes yielded greater imputation accuracies than shorter ones. When SNPs were selected based on linkage disequilibrium information, relative imputation accuracy was slightly improved. When 3000 and 10 000 equally spaced SNPs were used, the imputation accuracies were greater than 90% and approximately 97%, respectively. These results indicate that combining genotyping using a lower‐density SNP chip with genotype imputation based on a population of individuals genotyped using a higher‐density SNP chip is a cost‐effective and valid approach for genomic prediction.     

Gene dropping analysis of founder contributions in a closed Japanese black cattle population

Gene dropping simulation was applied to Japanese Black cattle population in Hyogo prefecture, to examine the survivals of alleles originated from founder animals. In the analysis, unique alleles were assigned to founders, and the genotypes of all descendants along the actual pedigree were generated through Monte Carlo simulation following Mendelian segregation rules. By replicating this process 10 000 times, the distribution of frequencies of alleles from each founder was estimated. From the distribution, several quantities useful for the management of genetic diversity, such as the probability of allele extinction and the probability of alleles surviving at a critically low frequency were derived. The materials used were 68 781 animals born in 1955–1998 and their pedigree records traced back to the population in 1937 or before. The expected number of alleles retained in the population drastically decreased during the analyzed period, and reached to 57.9 in the population of 1998, which was only 3.3% of the total number of alleles assigned to founders. Detailed analysis of major founders with relatively high genetic contributions to the current population revealed that alleles from most of the major founders are now at high risk of future extinction. These results strongly suggest that for the management of genetic diversity, the genetic contributions of founders are not fully informative, and emphasize the importance of the detection of live animals having founder alleles with high extinction possibilities.     

Detection of novel single-nucleotide polymorphisms (SNPs) in the CYP21 gene and association analysis of two SNPs for CYP21 and ESR2 with litter size in a commercial sow population

Altogether 129 F₁ sows from a commercial sow farm with at least four litters were genotyped for the oestrogen receptor 2 gene (ESR2) and cytochrome P450 hydroxylase 21 gene (CYP21) and investigated for associations on the litter‐size parameters: total number born and number born alive. Five novel polymorphisms were found in the 3′‐untranslated region for the CYP21 gene. Genotype and allele frequencies for the CYP21 (position 3462G > A) single‐nucleotide polymorphism (SNP) were 0.434 (GG), 0.504 (AG), 0.062 (AA) and 0.69 (G):0.31 (A), respectively. No association was found between this polymorphism and litter‐size parameters. For the ESR2 gene, the SNP in exon 5 associated with an amino acid substitution MET (allele A) > VAL (allele G) was investigated. Only two genotypes were found leading to allele frequencies of 0.34 (A):0.66 (G). Only number born alive piglets were significantly increased for the AG genotype (p = 0.034) with 11.64 piglets per sow and litter in comparison with the GG genotype, leading to only 10.96 piglets per sow and litter. From these data, it can be concluded that the investigated SNP of the ESR2 gene is associated with the number of liveborn piglets in the commercial population considered, and hence could be useful in selection for litter size. Therefore, this gene should be investigated in additional populations.     

Association of a single nucleotide polymorphism in the calpastatin gene with carcass and meat quality traits of beef cattle

Calpastatin (CAST) is a naturally occurring protein that inhibits the normal tenderization of meat as it ages postmortem. A SNP was identified in the CAST gene (a G to C substitution) and genotyped on crossbred commercially fed heifers (n = 163), steers (n = 226), and bulls (n = 61) from beef feedlots, and steers (n = 178) from a University of Guelph feeding trial. The association of the CAST SNP with carcass and meat quality traits was studied. Carcass traits included fat, lean, and bone yield; grade fat; LM area; and HCW. Meat quality traits included marbling grade; i.m. fat content of LM; tenderness evaluation of LM (Warner-Bratzler shear force) at 2, 7, 14, and 21 d of postmortem aging; and tenderness evaluation of semitendinosus muscle at 7 d of postmortem aging. The mixed model used in the analyses included fixed effects of CAST genotype, sex, slaughter group, and breed composition (linear covariate); sire was a random effect. For the analysis of shear force, i.m. fat content of LM was also included in the model as a linear covariate. Shear force measures were analyzed within days of postmortem aging and by repeated measures analysis. The CAST SNP allele C was more frequent (63%) in the crossbred population than allele G. The CAST SNP was associated with shear force across days of postmortem aging (P = 0.005); genotype CC yielded beef that was more tender than GG (-0.32 kg +/- 0.13), and CG had intermediate tenderness. The corresponding average allele substitution effect (G to C substitution) was also highly significant (-0.15 +/- 0.05 kg, P = 0.002). A lower percentage of unacceptably tough steaks (shear force > 5.7 kg) at 2 and 7 d postmortem was associated with an increasing number of C alleles (P < or = 0.05). At 7 d postmortem, the percentage of unacceptably tough steaks decreased by 24 and 35%, respectively, for animals carrying 1 and 2 copies of the C allele relative to animals with no C alleles. However, genotype CC had a greater fat yield (+1.44 +/- 0.56%; P = 0.037) than genotype GG, with a corresponding allele substitution effect of 0.67 +/- 0.27% (P = 0.015). Therefore, the CAST SNP allele C was associated with increased LM tenderness across days of postmortem aging and, importantly for the beef industry, had a significant reduction in the percentage of steaks rated unacceptably tough by consumers based on an assumed threshold level.     

Assessing single-nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle

A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single-nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger cattle using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen (1) at random, (2) with even genomic dispersion, (3) by maximizing the mean minor allele frequency (MAF), (4) using a combined score of MAF and linkage disequilibrium (LD), (5) using a partitioning-around-medoids (PAM) algorithm, and finally (6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen vs. a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) vs. 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01 < MAF ≤ 0.1) vs. high MAF (0.4 < MAF ≤ 0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the SA Drakensberger. Based on the results, a genotyping panel consisting of ~10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a <3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.     

Identification of differential selection traces in two Polish cattle breeds

Genetic improvement of animals based on artificial selection is leading to changes in the frequency of genes related to desirable production traits. The changes are reflected by the neutral, intergenic single nucleotide polymorphims (SNPs) being in long‐range linkage disequilibrium with functional polymorphisms. Genome‐wide SNP analysis tools designed for cattle, allow for scanning divergences in allelic frequencies between distinct breeds and thus for identification of genomic regions which were divergently selected in breeds' histories. In this study, by using Bovine SNP50 assay, we attempted to identify genomic regions showing the highest differences in allele frequencies between two distinct cattle breeds – preserved, unselected Polish Red breed and highly selected Holstein cattle. Our study revealed 19 genomic regions encompassing 55 protein‐coding genes and numerous quantitative trait loci which potentially may underlie some of the phenotypic traits distinguishing the breeds.     

Quantitative genotyping to estimate genetic contributions to pooled samples and genetic merit of the contributing entities

Abstract

Genotyping required to track family membership in aquaculture breeding programs is reduced dramatically by estimating the contributions of different families to pooled samples of tissue. This approach is relevant to widely differing scenarios involving animals, plants, and microbes. For the family membership scenario, SNP markers are genotyped for the contributing families' parents, and quantitatively genotyped to estimate allele frequencies within the mixed-family pooled tissue. Results are used to infer proportional contributions of the different families to the pool. Different computational strategies were tested for bias and sampling error. A correlation of 99% between estimated and true genetic contributions was achieved using 20 (50) randomly chosen SNPs at a standard error of allele frequency estimates of 0.01 (0.02). Optimal grouping of families and choice of markers further increases performance markedly. Trait means and distributions of families can be quite accurately estimated by tissue sampling across the range of trait values.