Multivariate analysis of mixed inheritance model of performance traits in layers using Gibbs sampling

The Gibbs sampling under a multitrait animal model was applied to detect the single gene affecting chicken performance traits and their pleiotropic actions as well as to estimate the heritability and correlations for these traits. A total of 14 823 individuals of a Rhode Island Red line (RIR) and 18 653 individuals of a Rhode Island White line (RIW) from six generations under long-term selection were recorded. Five performance traits were studied: initial egg production (IEP; until 38th week), egg production (until 54th week), egg weight at 33rd week (EW), age at first egg (AFE), and body weight at 20th week (BW). An analysis was based on the estimated marginal densities of the following parameters: frequencies, additive and dominance effects and variances and covariances (for single gene) as well as additive genetic and residual variances and respective covariances (for polygenes). An inference concerning the mixed inheritance model is performed by visualising the marginal posterior densities of major gene variance separately for all traits. The pleiotropic effect of single locus is expressed as the single gene correlation coefficient. It shows contributions of single genes to BW (10 and 15% of total variance for A22 and K44, respectively) and EW of K44 (9% of total variance). Moreover, a small positive pleiotropic single locus effect in line K44 was also registered. The polygenic heritability estimates obtained were low, except for EW and BW of both lines. Generally, the correlation estimates were in agreement with results reported in literature.     

Bayesian estimates of genetic changes for body weight traits of Moghani sheep using Gibbs sampling

The objective of the present study was to estimate genetic changes of body weight at different ages in Moghani sheep. Traits included were birth weight (BW, n = 4,208), 3-month weight (3MW, n = 4,175), 6-month weight (6MW, n = 3,138), 9-month weight (9MW, n = 2,244), and yearling weight (YW, n = 1,342). Data and pedigree information used in this study were collected at the Breeding Station of Moghani sheep during 1989–2005. The analysis was carried out for five traits, using the MTGSAM program. Breeding values of individual animals were obtained from a multivariate animal model analysis and genetic trends were obtained by regressing the means of predicted breeding values on year of birth for each trait. Direct genetic trends were positive and significant (P < 0.05) for BW, 3MW, 6MW, 9MW, and YW and were 1.63, 69.20, 79.38, 66.83, and 110.22 g/year, respectively. Also, maternal genetic trends for BW, 3MW, 6MW, 9MW, and YW were positive and significant (P < 0.05) and were 2.36, 49.18, 37.33, 17.73, and 9.67 g/year, respectively. The results showed that improvement of body weights of Moghani sheep seems feasible in selection programs.     

Estimation of genetic parameters and prediction of breeding values for multivariate threshold and continuous data in a simulated horse population using Gibbs sampling and residual maximum likelihood

Simulated horse data were used to compare multivariate estimation of genetic parameters and prediction of breeding values (BV) for categorical, continuous and molecular genetic data using linear animal models via residual maximum likelihood (REML) and best linear unbiased prediction (BLUP) and mixed linear-threshold animal models via Gibbs sampling (GS). Simulation included additive genetic values, residuals and fixed effects for one continuous trait, liabilities of four binary traits, and quantitative trait locus (QTL) effects and genetic markers with different recombination rates and polymorphism information content for one of the liabilities. Analysed data sets differed in the number of animals with trait records and availability of genetic marker information. Consideration of genetic marker information in the model resulted in marked overestimation of the heritability of the QTL trait. If information on 10,000 or 5,000 animals was used, bias of heritabilities and additive genetic correlations was mostly smaller, correlation between true and predicted BV was always higher and identification of genetically superior and inferior animals was - with regard to the moderately heritable traits, in many cases - more reliable with GS than with REML/BLUP. If information on only 1,000 animals was used, neither GS nor REML/BLUP produced genetic parameter estimates with relative bias 50% for all traits. Selection decisions for binary traits should rather be based on GS than on REML/BLUP breeding values.     

Combined use of phenotypic and genotypic information in sampling animals for genotyping in detection of quantitative trait loci.

Conventional selective genotyping which is using the extreme phenotypes (EP) was compared with alternative criteria to find the most informative animals for genotyping with respects to mapping quantitative trait loci (QTL). Alternative sampling strategies were based on minimizing the sampling error of the estimated QTL effect (MinERR) and maximizing likelihood ratio test (MaxLRT) using both phenotypic and genotypic information. In comparison, animals were randomly genotyped either within or across families. One hundred data sets were simulated each with 30 half-sib families and 120 daughters per family. The strategies were compared in these datasets with respect to estimated effect and position of a QTL within a previously defined genomic region at genotyping 10, 20 or 30% of the animals. Combined linkage disequilibrium linkage analysis (LDLA) was applied in a variance component approach. Power to detect QTL was significantly higher for both MinERR and MaxLRT compared with EP and random genotyping methods (either across or within family), for all the proportions of genotyped animals. Power to detect significant QTL (alpha = 0.01) with 20% genotyping for MinERR and MaxLRT was 80 and 75% of that obtained with complete genotyping compared with 70 and 38% genotyping for EP within and across families respectively. With 30% genotyping, the powers were 78, 83, 78 and 58% respectively. The estimated variance components were unbiased in EP strategies (within and across family), only when at least 30% was genotyped. To decrease the number of genotyped individuals either MinERR or MaxLRT could be considered. With 20% genotyping in MinERR, the estimated QTL variance components were not significant compared with complete genotype information but all studied strategies at 20% genotyping overestimated the QTL effect. Results showed that combining the phenotypic and genotypic information in selective genotyping (e.g. MinERR and MaxLRT) is better than using only the EPs and the combined methods can be considered as alternative approaches to decrease genotyping costs, with unbiased QTL effects, decreased sampling variance of the QTL variance component and also increased the power of QTL detection.     

Identifying single genes of large effect in quantitative traits using best linear unbiased prediction

The recent discovery of a major gene for rapid postweaning growth has reinforced the hypothesis that other quantitative continuous traits may be influenced by single genes of large effect. However, most methods for the detection of such genes rely on the discovery of multimodality in the population frequency distribution. The complicating effects of environment and artificial selection make the identification of such genes with field-collected data a formidable problem. An index is proposed that may serve as an indicator that a major gene is segregating within a population. The index is based on the assumption that under polygenic inheritance, an offspring's deviation from the midparent average is smaller than the deviation from either parent. Whereas, for the Mendelian segregation of a major gene, the opposite would be expected. A proposed class of indices is then based on the ratio [O - .5(S + D)]k/([O - S]k/2 [O - D]k/2) where O, S and D are the additive genetic values of an offspring and its sire and dam estimated via best linear unbiased prediction. Values of the index greater than 1. would be indicative of major gene inheritance. Simulation of small populations indicates that the index is quite sensitive to the existence of segregating major genes even in the absence of multimodality of the phenotypic distribution. However, the index remains dependent on the accuracy of genetic value estimation.     

Bayesian analysis of quantitative trait loci for boar taint in a Landrace outbred population

The genetic basis of the main components of boar taint was investigated in intact male pigs in a commercial population. We analyzed fat androsten-one and skatole concentrations from 217 males of an outbred Landrace population. Records were normalized using a logarithm transformation and tested for normality using a Wilk-Shapiro test. Bayesian analysis was then used to map QTL in 10 candidate regions previously selected on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 10, and 13. The criterion for QTL detection was the Bayes factor (BF) between polygenic models with and without QTL effects. Both traits had considerable genetic determination, with posterior means of total heritabilities ranging from 0.59 to 0.73 for androstenone and from 0.74 to 0.89 for skatole. Positive evidence for a fat skatole QTL was detected on SSC6 (BF = 5.16); however, no QTL for androstenone were found in any of the 10 chromosomal regions analyzed. With the detection of a QTL for the fat skatole concentration segregating in this population, marker-assisted selection or even gene-assisted selection could be used once the causal mutation of the QTL was identified.     

影响家畜繁殖性状主基因的研究进展

主基因是指能对数量性状产生巨大效应的单个基因或座位。家畜繁殖性状属低遗传力数量性状。通过对家畜繁殖性状主基因或其候选基因的定位、研究, 有利于进一步认识繁殖性状遗传机理, 加快对繁殖性状的改良速度。目前在猪上对FSHβ、ESR基因, 在绵羊上对FecB、FecX和BMP15等基因研究较多。     

Bayesian analysis of birth weight and litter size in Baluchi sheep using Gibbs sampling

Variance and covariance components for birth weight (BWT), as a lamb trait, and litter size measured on ewes in the first, second, and third parities (LS1 through LS3) were estimated using a Bayesian application of the Gibbs sampler. Data came from Baluchi sheep born between 1966 and 1989 at the Abbasabad sheep breeding station, located northeast of Mashhad, Iran. There were 10,406 records of BWT recorded for all ewe lambs and for ram lambs that later became sires or maternal grandsires. All lambs that later became dams had records of LS1 through LS3. Separate bivariate analyses were done for each combination of BWT and one of the three variables LS1 through LS3. The Gibbs sampler with data augmentation was used to draw samples from the marginal posterior distribution for sire, maternal grandsire, and residual variances and the covariance between the sire and maternal grandsire for BWT, variances for the sire and residual variances for the litter size traits, and the covariances between sire effects for different trait combinations, sire and maternal grandsire effects for different combinations of BWT and LS1 through LS3, and the residual covariations between traits. Although most of the densities of estimates were slightly skewed, they seemed to fit the normal distribution well, because the mean, mode, and median were similar. Direct and maternal heritabilities for BWT were relatively high with marginal posterior modes of .14 and .13, respectively. The average of the three direct-maternal genetic correlation estimates for BWT was low, .10, but had a high standard deviation. Heritability increased from LS1 to LS3 and was relatively high, .29 to .37. Direct genetic correlations between BWT and LS1 and between BWT and LS3 were negative, -.32 and -.43, respectively. Otherwise, the same correlation between BWT and LS2 was positive and low, .06. Genetic correlations between maternal effects for BWT and direct effects for LS1 through LS3 were all highly negative and consistent for all parities, circa -.75. Environmental correlations between BWT and LS1 through LS3 were relatively low and ranged from .18 to .29 and had high standard errors.     

Estimation of heritability for Tying-up syndrome in the Thoroughbred racehorse by Gibbs sampling

Tying‐up is a condition that primarily affects the muscles of horses. In this study, the heritability of the Tying‐up syndrome in the Thoroughbred racehorse was estimated by Bayesian analysis with Gibbs sampling based on the threshold model for binary traits. The data used were the clinical data in racehorses diagnosed by veterinarians of the Racehorse Clinics of Japan Racing Association from 2000 to 2003. The health status of the Tying‐up was treated as a binary trait. In the genetic analysis, the effect of changing the amount of the pedigree or inbreeding information on the estimation of heritability was investigated, too. The heritability estimates with non‐zero probability in the posterior densities were approximately 0.16–0.18 in minimum, suggesting that the heritability of the Tying‐up is not zero at least. The posterior density distributions of the heritability estimates were generally more pointed and sharp with using inbreeding coefficients than without using it, suggesting that more stable estimations were obtained when inbreeding coefficients were used. Among the different amounts of pedigree and inbreeding information, the heritabilities obtained with three or four generations of pedigree using inbreeding coefficients seems to be preferable, i.e. heritability of 0.42 or 0.43 for Tying‐up.     

影响羊毛性状和羊毛品质的主要基因和QTL的研究进展

羊毛细度、羊毛长度、羊毛强度以及弯曲度等性状都是影响羊毛品质的重要经济性状.用传统的技术改良这些性状需要较长的时间和费用,特别是对遗传力低的性状进行选择,很难精确估计此类数量性状座位的基因效应.     

Rapidly quantitative detection of Nosema ceranae in honeybees using ultra-rapid real-time quantitative PCR

BackgroundThe microsporidian parasite Nosema ceranae is a global problem in honeybee populations and is known to cause winter mortality. A sensitive and rapid tool for stable quantitative detection is necessary to establish further research related to the diagnosis, prevention, and treatment of this pathogen.ObjectivesThe present study aimed to develop a quantitative method that incorporates ultra-rapid real-time quantitative polymerase chain reaction (UR-qPCR) for the rapid enumeration of N. ceranae in infected bees.MethodsA procedure for UR-qPCR detection of N. ceranae was developed, and the advantages of molecular detection were evaluated in comparison with microscopic enumeration.ResultsUR-qPCR was more sensitive than microscopic enumeration for detecting two copies of N. ceranae DNA and 24 spores per bee. Meanwhile, the limit of detection by microscopy was 2.40 × 10⁴ spores/bee, and the stable detection level was ≥ 2.40 × 10⁵ spores/bee. The results of N. ceranae calculations from the infected honeybees and purified spores by UR-qPCR showed that the DNA copy number was approximately 8-fold higher than the spore count. Additionally, honeybees infected with N. ceranae with 2.74 × 10⁴ copies of N. ceranae DNA were incapable of detection by microscopy. The results of quantitative analysis using UR-qPCR were accomplished within 20 min.ConclusionsUR-qPCR is expected to be the most rapid molecular method for Nosema detection and has been developed for diagnosing nosemosis at low levels of infection.     

Dissection of additive genetic variability for quantitative traits in chickens using SNP markers

The aim of this study was to separate marked additive genetic variability for three quantitative traits in chickens into components associated with classes of minor allele frequency (MAF), individual chromosomes and marker density using the genomewide complex trait analysis (GCTA) approach. Data were from 1351 chickens measured for body weight (BW), ultrasound of breast muscle (BM) and hen house egg production (HHP), each bird with 354 364 SNP genotypes. Estimates of variance components show that SNPs on commercially available genotyping chips marked a large amount of genetic variability for all three traits. The estimated proportion of total variation tagged by all autosomal SNPs was 0.30 (SE 0.04) for BW, 0.33 (SE 0.04) for BM, and 0.19 (SE 0.05) for HHP. We found that a substantial proportion of this variation was explained by low frequency variants (MAF <0.20) for BW and BM, and variants with MAF 0.10–0.30 for HHP. The marked genetic variance explained by each chromosome was linearly related to its length (R² = 0.60) for BW and BM. However, for HHP, there was no linear relationship between estimates of variance and length of the chromosome (R² = 0.01). Our results suggest that the contribution of SNPs to marked additive genetic variability is dependent on the allele frequency spectrum. For the sample of birds analysed, it was found that increasing marker density beyond 100K SNPs did not capture additional additive genetic variance.     

Estimation of heritability for superficial digital flexor tendon injury by Gibbs sampling in the Thoroughbred racehorse

The superficial digital flexor tendon (SDFT) injury causes considerable wastage of racing Thoroughbreds. In this study, the heritability of SDFT injury of the forelimbs was estimated in the Thoroughbred racehorses based on the Bayesian analysis with Gibbs sampling using threshold animal models. New horse patients of SDFT injury at the age of 2–5 years accommodated in the training centers in 2005 were used for the analyses. Based on clinical data of 8198 horses, heritability of SDFT was estimated to be the order of 0.17 (posterior mode) to 0.19 ± 0.05 (posterior mean ± posterior SD).     

Estimation of heritability and genetic correlation for behavioural responses by Gibbs sampling in the Thoroughbred racehorse

Genetic variation of the behaviour of racehorses is one of the major concerns for racehorse breeders. In this study, the heritabilities of behavioural responses to the inspections of conjunctiva, auscultation and blood sampling and the genetic correlations among them were estimated in the Thoroughbred racehorse. The estimation was done with Bayesian analysis with Gibbs sampling based on the univariate or bivariate threshold animal models. The behavioural responses were scored with four categories at the first entrance quarantine in Miho Training Center of Japan Racing Association from 1993 to 1995. The behavioural responses were treated as categorical or binary traits, with both showing similar results. The estimated heritabilities were in the range of 0.23–0.28, suggesting a genetic component in the variation on these traits. The estimated genetic correlations among the traits were very high (approximately 0.9), suggesting that these behavioural responses may be measures of the same trait. Because of the high genetic correlations, repeatability threshold model was applied assuming the responses to be a genetically identical trait measured with three different tests. The estimated heritabilities (approximately 0.23) were at the lower bound of the former estimates. The revealed high repeatabilities (0.97–0.98) suggest a strong contribution of the individual temperament on the behaviour of racehorses.     

Identification of quantitative trait loci affecting female reproductive traits in a multigeneration Meishan-White composite swine population.

A multigeneration crossbred Meishan-White composite resource population was used to identify quantitative trait loci (QTL) for age at first estrus (AP) and the components of litter size: ovulation rate (OR; number of ova released in an estrous period) and uterine capacity (UC). The population was established by reciprocally mating Meishan (ME) and White composite (WC) pigs. Resultant F1 females were mated to either ME or WC boars to produce backcross progeny (BC) of either 3/4 WC 1/4 ME or 1/4 WC 3/4 ME. To produce the next generation (F3), 3/4 WC 1/4 ME animals were mated to 1/4 WC 3/4 ME animals yielding half-blood (1/2 WC 1/2 ME) progeny. A final generation (F4) was produced by inter se mating F3 animals. Measurements for AP and OR were recorded on 101 BC, 389 F3, and 110 F4 gilts, and UC data were from 101 BC and 110 F4 first parity litters. A genomic scan was conducted with markers (n = 157) spaced approximately 20 cM apart. All parental, F1, BC, and F4 animals but only 84 F3 animals were genotyped and included in this study. The QTL analysis fitted a QTL at 1-cM intervals throughout the genome, and QTL effects were tested using approximate genome-wide significance levels. For OR, a significant (E[false positive] < .05) QTL was detected on chromosome 8, suggestive (E[false positive] < 1.0) QTL were detected on chromosomes 3 and 10, and two additional regions were detected that may possess a QTL (E[false positive] < 2.0) on chromosomes 9 and 15. Two regions possessed suggestive evidence for QTL affecting AP on chromosomes 1 and 10, and one suggestive region on chromosome 8 was identified for UC. Further analyses of other populations of swine are necessary to determine the extent of allelic variation at the identified QTL.     

A new quantitative method for rabies virus by detection of nucleoprotein in virion using ELISA.

We have developed a new quantitative method for rabies virus (RV) detection using enzyme-linked immunosorbent assay (ELISA). The method named N-ELISA was based on the quantitation of nucleoprotein (N) in RV virions captured by RV-specific polyclonal antibodies on an ELISA plate. Both infective and defective interfering (DI) particles of RV could be detected by this method. When viruses were propagated in a medium of pH 7.4 adjusted with 7% NaHCO3, N-ELISA could detect them with titers of more than 10(6) pfu/ml, though the result did not correlate highly with that of the infectivity assay. The reason for this was considered to be that RVs included spikeless and damaged particles which were produced under conditions of low or high pH. However, in the time course of virus yield, titers of N-ELISA correlated well with those of the infectivity assay.     

Search for quantitative trait loci affecting growth and carcass traits in a cross population of beef and dairy cattle

A genome scan to detect QTL influencing growth and carcass-related traits was conducted in a Charolais x Holstein crossbred cattle population. Phenotypic measurements related to growth and carcass traits were made on the 235 second-generation crossbred males of this herd (F2 and reciprocal backcrosses), which were born in 4 consecutive annual cohorts. Traits measured in vivo were related to birth dimensions, growth rates, and ultrasound measurements of fat and muscle depth. The animals were slaughtered near a target BW of 550 kg, and a wide range of postmortem traits were measured: visual assessment of carcass conformation and carcass fatness, estimated subcutaneous fat percentage, weights of kidney knob and channel fat, and weights of carcass components after commercial and full-tissue dissections. The whole population, including grandparents, parents, and the crossbred bulls, was genotyped initially for 139 genome-wide microsatellite markers. Twenty-six additional markers were subsequently analyzed to increase marker density on some of the chromosomes where QTL had been initially identified. The linear regression analyses based on the 165 markers revealed a total of 51 significant QTL at the suggestive level, 21 of which were highly significant (F-value >or=9; based on the genome-wide thresholds obtained in the initial scan). A large proportion of the highly significant associations were found on chromosomes 5 and 6. The most highly significant QTL was localized between markers DIK1054 and DIK082 on chromosome 6 and explained about 20% of the phenotypic variance for the total bone proportion estimated after the commercial dissection. In the adjacent marker interval on this chromosome, 2 other highly significant QTL were found that explain about 30% of the phenotypic variance for birth dimension traits (BW and body length at birth). On chromosome 5, the most significant association influenced the lean:bone ratio at the forerib joint and was flanked by markers DIK4782 and BR2936. Other highly significant associations were detected on chromosomes 10 (estimated subcutaneous fat percentage), 11 (total saleable meat proportion), 16 (prehousing growth rate), and 22 (bone proportion at the leg joint). These results provide a useful starting point for the identification of the genes associated with traits of direct interest to the beef industry, using fine mapping or positional candidate gene approaches.     

发生马铃薯立枯病土壤中立枯丝核菌的荧光定量PCR快速检测

连作马铃薯根际土壤中立枯丝核菌的大量累积可能是导致马铃薯连作障碍发生的主要原因之一。为了解根际土壤中土传病害病原菌的积累与连作障碍之间的关系,进一步寻求缓解和克服马铃薯连作障碍土传病害的有效途径,本研究建立优化了荧光定量PCR(real-time PCR)方法,对引起马铃薯立枯病的病原菌立枯丝核菌进行了快速监测和绝对定量,对马铃薯连作1～5年根际土壤立枯丝核菌的动态变化趋势进行了检测分析。结果显示,研究建立优化的荧光定量PCR检测方法,可直接应用土壤DNA进行病原菌的定量检测,能检测到土壤中浓度为1×10²个拷贝/g土的马铃薯立枯丝核菌,扩增效率为1.04,具有检出限低、扩增效率高的特点,实现了不通过病土分离培养方法,就可掌握病原菌在根际土壤中的累积状况;在马铃薯立枯病发病严重的连作根际土壤中,立枯丝核菌的累积数量随连作年限的递增呈上升趋势;病原菌的累积随生育进程的推进呈下降趋势;病原菌累积量最大的是连作5年的播前土壤,每g土壤达3.75×10⁷个拷贝数,由此可见,连作导致了土壤微生物种群结构发生改变,土壤致病真菌数量增加,相应地也增加了马铃薯立枯病的初侵染机率。