动物模型及多性状BLUP在家禽遗传鉴定中的应用

利用最佳线性无偏预测法(BLUP)估计家畜的育种值,目前除家禽外已在其它各家畜中得到了广泛的应用。本文利用动物模型和多性状BLUP对“京白Ⅰ系”蛋鸡在1986—1987年24个家系的777个个体的系统分组资料进行了分析,估计出了所有个体的复合育种值。其中考虑了两个性状(40周产蛋数和36周蛋重)和两个固定效应(鸡舍-鸡笼效应和孵化批次效应)。同时还对混合模型方程组维数较大时如何在微机上实现进行了研究,即(1)利用磁盘存取系数矩阵的非零元素和中间计算结果;(2)简化了多性状BLUP的计算,利用乔列斯基(Cholesky)分解变换后,此法建立的方程数是常规算法方程数的1/q(q为性状数);(3)简化了方程组迭代求解的方法,即利用块迭代法,这样大大缩短了计算的机吋,节省了费用,使BLUP在家禽中的推广应用成为可能。     

Isozymes,plant population genetic structure and genetic conservation

Summary The exploration, conservation and use of the genetic resources of plants is a contemporary issue which requires a multidisciplinary approach. Here the role of population genetic data, particularly those derived from electrophoretic analysis of protein variation, is reviewed. Measures of the geographic structure of genetic variation are used to check on sampling theory. Current estimates justify the contention that alleles which have a highly localised distribution, yet are in high frequency in some neighbourhoods, represent a substantial fraction of the variation. This class, which is the most important class in the framing of sampling strategies, accounts for about 20–30% of variants found in 12 plant species. The importance of documenting possible coadapted complexes and gene-environment relationships is discussed. Furthermore, the genetic structure of natural populations of crop relatives might suggest the best structure to use in the breeding of crops for reduced vulnerability to pest and disease attack, or for adaptation to inferior environments. The studies reported to date show that whilst monomorphic natural populations do occur, particularly in inbreeding colonisers, or at the extreme margins of the distribution, polymorphism seems to be the more common mode. It is stressed here that the genetic resources of the wild relatives of crop plants should be systematically evaluated. These sources will supplement, and might even rival, the primitive land races in their effectiveness in breeding programmes. We may look forward to a wider application of gel electrophoresis in the evaluation of plant genetic resources because this technique is currently the best available for detecting genetic differences close to the DNA level on samples of reasonable size.     

Evidence for frequent incest in a cooperatively breeding mammal

As breeding between relatives often results in inbreeding depression, inbreeding avoidance is widespread in the animal kingdom. However, inbreeding avoidance may entail fitness costs. For example, dispersal away from relatives may reduce survival. How these conflicting selection pressures are resolved is challenging to investigate, but theoretical models predict that inbreeding should occur frequently in some systems. Despite this, few studies have found evidence of regular incest in mammals, even in social species where relatives are spatio-temporally clustered and opportunities for inbreeding frequently arise. We used genetic parentage assignments together with relatedness data to quantify inbreeding rates in a wild population of banded mongooses, a cooperatively breeding carnivore. We show that females regularly conceive to close relatives, including fathers and brothers. We suggest that the costs of inbreeding avoidance may sometimes outweigh the benefits, even in cooperatively breeding species where strong within-group incest avoidance is considered to be the norm.     

Haplotype inference in crossbred populations without pedigree information

Background

Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.

Results

We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.

Conclusion

Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.     

Simulation of gene pyramiding in Drosophila melanogaster

Gene pyramiding has been successfully practiced in plant breeding for developing new breeds or lines in which favorable genes from several different lines were integrated.But it has not been used in animal breeding,and some theoretical investigation and simulation analysis with respect to its strategies,feasibility and efficiency are needed before it can be implemented in animals.In this study,we used four different pure fines of Drosophila melanogaster,each of which is homozygous at a specific mutant gene with a visible effect on phenotype,to simulate the gene pyramiding process and analyze the duration and population size required in different pyramiding strategies.We finally got the ideal individuals,which are homozygous at the four target genes simultaneously.This study demonstrates that gene pyramiding is feasible in animal breeding and the interaction between genes may affect the final results.     

Use of the numerator relationship matrix in genetic analysis of autopolyploid species

Mixed models incorporating the inverse of a numerator relationship matrix (NRM) are widely used to estimate genetic parameters and to predict breeding values in animal breeding. A simple and quick method to directly calculate the inverse of the NRM has been historically developed for diploid animal species. Mixed models are less used in plant breeding partly because the existing method for diploids is not applicable to autopolyploid species. This is because of the phenomenon of double reduction and the possibility that gametes carry alleles which are identical by descent. This paper generalises the NRM and its inverse for autopolyploid species, so it can be easily incorporated into their genetic analysis. The technique proposed is to first calculate the kinship coefficient matrix and its inverse as a precursor to calculating the NRM and its inverse. This allows the NRM to be calculated for populations containing individuals of mixed ploidy levels. This generalization can also accommodate uncertain parentage by generating the “average” relationship matrix. The possibility that non-inbred parents can produce inbred progeny (double reduction) is also discussed. Rules are outlined that are applicable for any level of ploidy. Examples of use of the matrix are provided using simulated pedigrees.     

Canadian regulatory aspects of gene editing technologies

The development of gene editing techniques, capable of producing plants and animals with new and improved traits, is revolutionizing the world of plant and animal breeding and rapidly advancing to commercial reality. However, from a regulatory standpoint the Government of Canada views gene editing as another tool that will join current methods used to develop desirable traits in plants and animals. This is because Canada focusses on the potential risk resulting from the novelty of the trait, or plant or animal product entering the Canadian environment or market place, rather than the process or method by which it was created. The Canadian Food Inspection Agency is responsible for the regulation of the environmental release of plants with novel traits, and novel livestock feeds, while Health Canada is responsible for the regulation of novel foods. Environment and Climate Change Canada, in partnership with Health Canada, regulates modified animals for entry into the environment. In all cases, these novel products may be the result of conventional breeding, mutagenesis, recombinant DNA techniques or other methods of plant or animal breeding such as gene editing. This novelty approach allows the Canadian regulatory system to efficiently adjust to any new developments in the science of plant and animal breeding and allows for risk-appropriate regulatory decisions. This approach encourages innovation while maintaining science-based regulatory expertise. Canadian regulators work cooperatively with proponents to determine if their gene editing-derived product meets the definition of a novel product, and whether it would be subject to a pre-market assessment. Therefore, Canada’s existing regulatory system is well positioned to accommodate any new innovations or technologies in plant or animal breeding, including gene editing.

     

Planning incomplete block experiments when treatments are genetically related

Selection trials in plant and animal breeding, in incomplete blocks, are described by linear models with random effect parameters associated with treatments with known genetic covariance structure. It is now well known that the information on relatives can improve the analysis and many extensions of this model have been proposed, but no studies have been done on the consequences of this genetical relatedness among treatments for the optimality of block designs. Using a suitable optimality criterion, we show that the knowledge on relatedness may imply that the optimal design is not in the class of designs which are optimal for unrelated treatments. Implications for practical applications are discussed.     

Gene dispersal and outbreeding in a philopatric mammal

Extensive mark-recapture data from banner-tailed kangaroo rats, Dipodomys spectabilis, have shown that both males and females are highly philopatric and suggest the possibility of close inbreeding. However, indirect analyses based on genetic structure appear to contradict direct observations, suggesting longer dispersal distances. Using microsatellite genotypes from most members of a banner-tailed kangaroo rat population during five successive breeding seasons, we ask how relatedness is influenced by dispersal and how it in turn influences mating patterns. The data confirm that, because of philopatry, neighbours are often close relatives. However, patterns of parentage also show that the average distance between mates is large relative to natal dispersal distances and larger than the average distance between nearest opposite-sexed neighbours. Females' mates were often not their nearest male neighbour and many were less related than the nearest male neighbour. We detected multiple paternity in some females' litters; both sexes produce offspring with multiple mates within and between breeding seasons. At the population level, heterozygosities were high and estimates of F were low, indicating that levels of inbreeding were low. Using individual inbreeding coefficients of all juveniles to estimate their parents' relatedness, we found that parental relatedness was significantly lower than relatedness between nearest opposite-sexed adult neighbours. Thus in philopatric populations, long breeding forays can cause genes to move further than individuals disperse, and polyandry may serve to reduce relatedness between mates.     

Locally Epistatic Genomic Relationship Matrices for Genomic Association and Prediction

In plant and animal breeding studies a distinction is made between the genetic value (additive plus epistatic genetic effects) and the breeding value (additive genetic effects) of an individual since it is expected that some of the epistatic genetic effects will be lost due to recombination. In this article, we argue that the breeder can take advantage of the epistatic marker effects in regions of low recombination. The models introduced here aim to estimate local epistatic line heritability by using genetic map information and combining local additive and epistatic effects. To this end, we have used semiparametric mixed models with multiple local genomic relationship matrices with hierarchical designs. Elastic-net postprocessing was used to introduce sparsity. Our models produce good predictive performance along with useful explanatory information.     

Methods to estimate breeding values in honey bees

Background

Efficient methodologies based on animal models are widely used to estimate breeding values in farm animals. These methods are not applicable in honey bees because of their mode of reproduction. Observations are recorded on colonies, which consist of a single queen and thousands of workers that descended from the queen mated to 10 to 20 drones. Drones are haploid and sperms are copies of a drone’s genotype. As a consequence, Mendelian sampling terms of full-sibs are correlated, such that the covariance matrix of Mendelian sampling terms is not diagonal.

Results

In this paper, we show how the numerator relationship matrix and its inverse can be obtained for honey bee populations. We present algorithms to derive the covariance matrix of Mendelian sampling terms that accounts for correlated terms. The resulting matrix is a block-diagonal matrix, with a small block for each full-sib family, and is easy to invert numerically. The method allows incorporating the within-colony distribution of progeny from drone-producing queens and drones, such that estimates of breeding values weigh information from relatives appropriately. Simulation shows that the resulting estimated breeding values are unbiased predictors of true breeding values. Benefits for response to selection, compared to an existing approximate method, appear to be limited (~5%). Benefits may however be greater when estimating genetic parameters.

Conclusions

This work shows how the relationship matrix and its inverse can be developed for honey bee populations, and used to estimate breeding values and variance components.     

Estimation of quantitative genetic parameters

This paper gives a short review of the development of genetic parameter estimation over the last 40 years. The need to analyse genetic processes in both animal selection experiments and animal breeding improvement programmes motivated the majority of this work. The usage of animal model in conjunction with residual maximum likelihood (REML) techniques for mixed models has revolutionized the methods. These methods to estimate quantitative genetic parameters have recently been advocated for use in evolutionary studies of natural populations. Therefore, it is perhaps timely to discuss the development of REML methods and their application to the analysis of artificial selection experiments and breeding programmes in animals. This should give extra insight into the methods and hopefully lead to synergy between both the areas.     

A General Unified Framework to Assess the Sampling Variance of Heritability Estimates Using Pedigree or Marker-Based Relationships

Heritability is a population parameter of importance in evolution, plant and animal breeding, and human medical genetics. It can be estimated using pedigree designs and, more recently, using relationships estimated from markers. We derive the sampling variance of the estimate of heritability for a wide range of experimental designs, assuming that estimation is by maximum likelihood and that the resemblance between relatives is solely due to additive genetic variation. We show that well-known results for balanced designs are special cases of a more general unified framework. For pedigree designs, the sampling variance is inversely proportional to the variance of relationship in the pedigree and it is proportional to 1/N, whereas for population samples it is approximately proportional to 1/N², where N is the sample size. Variation in relatedness is a key parameter in the quantification of the sampling variance of heritability. Consequently, the sampling variance is high for populations with large recent effective population size (e.g., humans) because this causes low variation in relationship. However, even using human population samples, low sampling variance is possible with high N.     

Female reproductive competition in Eulemur rufifrons: eviction and reproductive restraint in a plurally breeding Malagasy primate

In mammals with female philopatry, co-resident females inevitably compete with each other for resources or reproductive opportunities, thereby reducing the kin-selected benefits of altruism towards relatives. These counteracting forces of cooperation and competition among kin should be particularly pronounced in plurally breeding species with limited alternative breeding opportunities outside the natal group. However, little is still known about the costs of reproductive competition on females' fitness and the victims' potential counter-strategies. Here we summarize long-term behavioural, demographic and genetic data collected on a plurally breeding primate from Madagascar to illuminate mechanisms and effects of female reproductive competition, focusing on forcible eviction and potential reproductive restraint. The main results of our study indicate that females in groups of redfronted lemurs (Eulemur rufifrons) above a critical size suffer from competition from their close relatives: females in larger groups face an increased probability of not giving birth as well as a higher probability of being evicted, especially during the annual mating and birth seasons. Eviction is not predicted by the number of adult females, the number of close female relatives, female age or inter-annual variation in rainfall but only by total group size. Thus, eviction in this species is clearly linked with reproductive competition, it cannot be forestalled by reproductive restraint or having many relatives in the group, and it occurs in the absence of a clear dominance hierarchy. Our study therefore also underscores the notion that potential inclusive fitness benefits from living with relatives may have been generally over-rated and should not be taken for granted.     

Application of Genomics Tools to Animal Breeding

The main goal in animal breeding is to select individuals that have high breeding values for traits of interest as parents to produce the next generation and to do so as quickly as possible. To date, most programs rely on statistical analysis of large data bases with phenotypes on breeding populations by linear mixed model methodology to estimate breeding values on selection candidates. However, there is a long history of research on the use of genetic markers to identify quantitative trait loci and their use in marker-assisted selection but with limited implementation in practical breeding programs. The advent of high-density SNP genotyping, combined with novel statistical methods for the use of this data to estimate breeding values, has resulted in the recent extensive application of genomic or whole-genome selection in dairy cattle and research to implement genomic selection in other livestock species is underway. The high-density SNP data also provides opportunities to detect QTL and to encover the genetic architecture of quantitative traits, in terms of the distribution of the size of genetic effects that contribute to trait differences in a population. Results show that this genetic architecture differs between traits but that for most traits, over 50% of the genetic variation resides in genomic regions with small effects that are of the order of magnitude that is expected under a highly polygenic model of inheritance.     

Genetic Distances Based on Quantitative Traits

Morphological data showing continuous distributions, polygenically controlled, may be particularly useful in intergroup classification below the species level; an appropriate distance analysis based on these traits is an important tool in evolutionary biology and in plant and animal breeding.--The interpretation of morphological distances in genetic terms is not easy because simple phenotypic data may lead to biased estimates of genetic distances. Convenient estimates can be obtained whenever it is possible to breed populations according to a suitable crossing design and to derive information from genetic parameters.--A general method for determining genetic distances is proposed. The procedure of multivariate analysis of variance is extended to estimate appropriate genetic parameters (genetic effects). Not only are optimal statistical estimates of parameters obtained but also the procedure allows the measurement of genetic distances between populations as linear functions of the estimated parameters, providing an appropriate distance matrix that can be defined in terms of these parameters. The use of the T2 statistic, defined in terms of the vector of contrasts specifying the distance, permits the testing of the significance of any distance between any pair of populations that may be of interest from a genetic point of view.--A numerical example from maize diallel data is reported in order to illustrate the procedure. In particular, heterosis effects are used as the basis for estimates of genetic divergence between populations.     

Estimating genetic correlations in natural populations in the absence of pedigree information: accuracy and precision of the Lynch method

Usually, genetic correlations are estimated from breeding designs in the laboratory or greenhouse. However, estimates of the genetic correlation for natural populations are lacking, mostly because pedigrees of wild individuals are rarely known. Recently Lynch (1999) proposed a formula to estimate the genetic correlation in the absence of data on pedigree. This method has been shown to be particularly accurate provided a large sample size and a minimum (20%) proportion of relatives. Lynch (1999) proposed the use of the bootstrap to estimate standard errors associated with genetic correlations, but did not test the reliability of such a method. We tested the bootstrap and showed the jackknife can provide valid estimates of the genetic correlation calculated with the Lynch formula. The occurrence of undefined estimates, combined with the high number of replicates involved in the bootstrap, means there is a high probability of obtaining a biased upward, incomplete bootstrap, even when there is a high fraction of related pairs in a sample. It is easier to obtain complete jackknife estimates for which all the pseudovalues have been defined. We therefore recommend the use of the jackknife to estimate the genetic correlation with the Lynch formula. Provided data can be collected for more than two individuals at each location, we propose a group sampling method that produces low standard errors associated with the jackknife, even when there is a low fraction of relatives in a sample.     

No evidence of inbreeding avoidance despite demonstrated survival costs in a polygynous rodent

Individuals are generally predicted to avoid inbreeding because of detrimental fitness effects. However, several recent studies have shown that limited inbreeding is tolerated by some vertebrate species. Here, we examine the costs and benefits of inbreeding in a largely polygynous rodent, the yellow-bellied marmot (Marmota flaviventris). We use a pedigree constructed from 8 years of genetic data to determine the relatedness of all marmots in our study population and examine offspring survival, annual male reproductive success, relatedness between breeding pairs and the effects of group composition on likelihood of male reproduction to assess inbreeding in this species. We found decreased survival in inbred offspring, but equal net reproductive success among males that inbred and those that avoided it. Relatedness between breeding pairs was greater than that expected by chance, indicating that marmots do not appear to avoid breeding with relatives. Further, male marmots do not avoid inbreeding: males mate with equal frequency in groups composed of both related and unrelated females and in groups composed of only female relatives. Our results demonstrate that inbreeding can be tolerated in a polygynous species if the reproductive costs of inbreeding are low and individuals that mate indiscriminately do not suffer decreased reproductive success.     

Recent progress in livestock genomics and potential impact on breeding programs

Most of the major livestock breeding organizations in the world are actively involved in using the emerging tools for genome analysis to obtain a better understanding of the molecular architecture of their favourite production traits. This is bound to generate a considerable amount of novel biological information that will provide a competitive advantage to those that have access to it. At present, the preferred avenue to exploit this information is via marker-assisted selection (MAS), and several breeding organisations are starting to implement MAS in breeding programs. However, it seems unlikely that the exploitation of genomics information will be limited to MAS in the future. Even though it is difficult to anticipate the ultimate impact of genomics on animal production, it would be very surprising if it were not to revolutionize this industry as it is already revolutionizing the biomedical and plant breeding industries.     

Factor analytic and reduced animal models for the investigation of additive genotype-by-environment interaction in outcrossing plant species with application to a Pinus radiata breeding programme

Key message

Modelling additive genotype-by-environment interaction is best achieved with the use of factor analytic models. With numerous environments and for outcrossing plant species, computation is facilitated using reduced animal models.

Abstract

The development of efficient plant breeding strategies requires a knowledge of the magnitude and structure of genotype-by-environment interaction. This information can be obtained from appropriate linear mixed model analyses of phenotypic data from multi-environment trials. The use of factor analytic models for genotype-by-environment effects is known to provide a reliable, parsimonious and holistic approach for obtaining estimates of genetic correlations between all pairs of trials. When breeding for outcrossing species the focus is on estimating additive genetic correlations and effects which is achieved by including pedigree information in the analysis. The use of factor analytic models in this setting may be computationally prohibitive when the number of environments is moderate to large. In this paper, we present an approach that uses an approximate reduced animal model to overcome the computational issues associated with factor analytic models for additive genotype-by-environment effects. The approach is illustrated using a Pinus radiata breeding dataset involving 77 trials, located in environments across New Zealand and south eastern Australia, and with pedigree information on 315,581 trees. Using this approach we demonstrate the existence of substantial additive genotype-by-environment interaction for the trait of stem diameter measured at breast height. This finding has potentially significant implications for both breeding and deployment strategies. Although our approach has been developed for forest tree breeding programmes, it is directly applicable for other outcrossing plant species, including sugarcane, maize and numerous horticultural crops.