Efficient computation of genotype probabilities for loci with many alleles: II. Iterative method for large, complex pedigrees

An algorithm for computing genotype probabilities for marker loci with many alleles in large, complex pedigrees with missing marker data is presented. The algorithm can also be used to calculate grandparental origin probabilities, which summarize the segregation pattern and are useful for mapping quantitative trait loci. The algorithm is iterative and is based on peeling on alleles instead of the traditional peeling on genotypes. This makes the algorithm more computationally efficient for loci with many alleles. The algorithm is approximate in pedigrees that contain loops, including loops generated by full sibs. The algorithm has no restrictions on pedigree structure or missing marker phenotypes, although together those factors affect the degree of approximation. In livestock pedigrees with dense marker data, the degree of approximation may be minimal. The algorithm can be used with an incomplete penetrance model for marker loci. Thus, it takes into account the possibility of marker scoring errors and helps to identify them. The algorithm provides a computationally feasible method to analyze genetic marker data in large, complex livestock pedigrees.     

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.     

Sampling genotype configurations in a large complex pedigree

Many genetic problems can be solved by Monte Carlo method. This often requires sampling genotype configurations over pedigree. Current available samplers are inefficient for large animal pedigrees. A new sampler suitable for large complex pedigrees has been developed and evaluated. The sampler uses simple and iterative peeling algorithms alternately. The sampler was compared to two other samplers on hypothetical pedigree of 79 individuals and recessive disease. The behaviour of the sampler was evaluated in four experimental designs on real bovine pedigree of 907,903 animals. The application of the sampler was also exemplified in identical by descent study.     

Genetic evaluation using parentage information from genetic markers

Genetic evaluation relies on pedigree information to account for the trait information on individuals and their relatives. Recording pedigrees may place unfavorable restrictions on the management of breeding populations, such as the use of single-sire mating groups and the observation of parturition. The use of DNA marker information is an alternative method to identify parents, but it is difficult to assign the parents unambiguously for all progeny in extensively farmed livestock without the use of very many markers. We present methods that use DNA information on parentage within a genetic evaluation system that allow for genotyping errors and for the parentage information to be incomplete, with probabilities assigned to possible parent pairs (i.e., fractional parentage assignment). Two of these methods use a computing strategy that circumvents the high memory requirements associated with the application of previous methods designed for use with fractional parentage assignment. This strategy has an additional advantage of allowing the same statistical models to be used in the evaluation as with recorded pedigrees. The use of DNA marker-based parentage for genetic evaluation is associated with lower genetic gain (at the same survival levels) than by using the true pedigree. This decrease in gain depends on a number of factors, including trait heritability and the DNA markers used. The methods we have described show how DNA marker information could be used to replace traditional pedigree recording.     

绒山羊X染色体7个微卫星标记的遗传连锁图谱的构建

本研究利用内蒙古白绒山羊的7个父系半同胞家系共794个个体,用X染色体上的7个微卫星标记进行了系谱确认,构建了绒山羊X染色体遗传连锁图。结果表明,7个标记的等位基因数变化范围为9～14,杂合度在0.585～0.918之间,平均杂合度为0.726;多态信息含量在0.759～0.897之间,平均多态信息含量为0.834。构建的内蒙古白绒山羊X染色体遗传连锁图总长度139.4 cM,与英国罗斯林研究所公布的SM4.7绵羊连锁图标记顺序一致,可用于下一步的QTL定位研究。     

草原红牛及其杂交群体中微卫星DNA多态性研究

选用草原红牛及其与利木赞牛的杂交后代66头作为试验牛群体,提取血液及肝脏基因组DNA,设计8对微卫星引物进行PCR扩增,从分子水平上对草原红牛及其杂交群体8个位点的遗传多态性进行微卫星分析。结果表明,在草原红牛中,ETH225、IDVGA2、IDVGA46和IDVGA44等位基因数分别为5、4、3和4,多态信息含量(PIC)分别为0．5420、0．6736、0．5218和0．5750,这4个位点均为高度多态。而另4个位点BM2113、BM1824、IDVGA55和TGLA44等位基因数分别,2、2、2和5,多态信息含量分别为0．3698、0．3604、0．3538和0．4708,属于中度多态性位点。在杂交牛群体中,BM2113、ETH225、IDVGA2、IDVGA46、ID- VGA44、BM1824、IDVGA55和TGLA44这8个位点的等位基因数分别为4、5、4、4、5、4、4和6,多态信息含量(PIC)分别为0．6432、0．5943、0．6593、0．5794、0．7259、0．6121、0．6120和0．6204,杂合度为0．7034,均属于高度多态性位点。这些微卫星位点作为遗传标记应用于草原红牛遗传育种研究之中是可行的。     

Estimation of linkage disequilibrium in a sample of the United Kingdom dairy cattle population using unphased genotypes

The association between genetic marker alleles was estimated for two regions of the bovine genome from a random sample of 50 young dairy bulls born in the United Kingdom between 1988 and 1995. Microsatellite marker genotypes were obtained for six markers on chromosome 2 and seven markers on chromosome 6, spanning 38 and 20 cM, respectively. Two different methods, which do not require family information, were used to estimate population haplotype frequencies. Haplotype frequencies were estimated for pairs of loci using the expectation-maximization algorithm and for all linked loci using a Bayesian approach via a Markov chain-Monte Carlo algorithm. Significant (P = 0.0007) linkage disequilibrium was detected between pairs of loci in syntenic groups (that is, loci in the same linkage group), extending to about 10 cM. No significant linkage disequilibrium was detected between markers in nonsyntenic regions. Given the observed level of linkage disequilibrium, mapping methods based on population-wide association might provide a better resolution than traditional quantitative trait loci mapping methods in the U.K. dairy cattle population and may reduce the required sample sizes of the experiments.     

Introgressing multiple QTL in breeding programmes of limited size.

The ability to enrich a breed with favourable alleles from multiple unlinked quantitative trait loci (QTL) of a donor breed through marker-assisted introgression (MAI) in a population of limited size was evaluated by considering the effects of the proportion selected, the size of the marker intervals, the number of introgressed QTL and the uncertainty of QTL position. Informative flanking markers were used to select progeny with the largest expected number of donor QTL alleles over five generations of backcrossing and five generations of intercrossing. In the backcrossing phase, with 5% selected and 20 cM marker intervals for three QTL, there were sufficient backcross progeny that were heterozygous for all markers, and QTL frequencies dropped below 0.5 only because of double recombinants. For higher fractions selected, longer marker intervals, and more QTL, frequency reductions from 0.5 were greater and increased with additional generations of backcrossing. However, even with 20% selected, three QTL, and marker intervals of 5 or 20 cM, mean QTL frequencies in generation 5 were 0.35 and 0.30, sufficient to allow subsequent selection of QTL in the intercrossing phase. After five generations of intercrossing, over 90% of individuals were homozygous for all QTL, and 85% when five QTL were introgressed. The higher the proportions selected, the longer the marker intervals, and larger numbers of introgressed QTL increased the number of intercrossing generations required to achieve fixation of QTL. Location of the QTL in the marked intervals did not affect QTL frequencies or the proportion of QTL lost at the end of the introgression programme. In conclusion, introgressing multiple QTL can be accomplished in a MAI programme of limited size without requiring that all individuals selected during the backcrossing phase to be carriers of favourable alleles at all QTL.     

A genotype probability index for multiple alleles and haplotypes

We use linear algebra to calculate an index of information content in genotype probabilities which has previously been calculated using trigonometry. The new method can be generalized allowing the index to be calculated for loci with more than two alleles. Applications of this index include its use in genotyping strategies, strategies to manage genetic disorders and in estimation of genotype effects.     

Estimating allelic richness and its diversity

Assessing allelic richness in a set of populations requires that variations of sample size be taken into account. One way of doing this is to estimate the number of alleles expected in samples of specified size, using the rarefaction method applied in ecology. An alternative method, based on extrapolation, consists of adding to the number of alleles actually seen in a population the expected number of alleles missing, given the number of genes examined in the population and the allelic frequencies observed over the whole set of populations. Heterogeneity of allelic richness across populations and across loci can also be tested in this framework by numerical re-sampling. Both methods provide a measure of “private” allelic richness, a useful criterion in genetic diversity preservation, by allowing evaluation of the uniqueness of each population in terms of allele numbers. The two methods are compared on isozyme loci in the argan tree of Morocco and on microsatellite genotypes in the European pig. In both species, allelic richness and gene diversity behave quasi-independently over the populations compared and a higher differentiation is observed in allelic richness compared to gene diversity. In general, the rarefaction technique is sensitive to the sample size of reference and may lack sensitivity to rare alleles when the sample size of reference is small. Extrapolation may thus be recommended especially when the sample sizes of the populations are either low on average or highly unbalanced among populations.     

4个猪繁殖性状候选基因对大白猪产活仔数的影响

为研究猪繁殖性状候选主效基因的遗传效应并应用于猪的繁殖性状改良,实验选择472头大白能繁母猪作为基础群,检测4个控制猪繁殖性状的候选主效基因ESR、FSHβ、PRLR和RBP4在该群体的多态性分布及其对产活仔数的影响.结果表明:除RBP4基因为AA纯合子外,ESR、PSHIS、PRLR 3个基因均存在不同程度的多态,并...     

草原红牛群体中微卫星DNA多态性的研究

选用草原红牛42头作为试验牛群体,经过牛血液基因组DNA的提取、8对微卫星引物的PCR扩增、扩增产物的聚丙烯酰胺电泳分型、UVIBAND计算机凝胶成像分析系统分析各位点等位基因及全部个体的标记基因型、PPAP3.0软件计算基因频率、多态信息含量(PIC)和杂合度等步骤,从分子水平上分析了草原红牛在8个位点的遗传多态性。结果表明,ETH225、IDVGA2、IDVGA46和IDVGA44等位基因数分别为5、4、3和4,多态信息含量分别为0.542 0,0.673 6,0.521 8和0.575 0,这4个位点为高度多态位点。而另4个位点BM2113、BM1824、IDVGA55和TGLA44等位基因数分别2、2、2和5,多态信息含量分别为0.369 8,0.360 4,0.353 8和0.470 8,属于中度多态性位点。8个位点作为遗传标记应用于草原红牛遗传育种研究之中是可行的。     

利用微卫星标记鉴定德州驴亲子关系

试验旨在建立一套适用于德州驴亲子关系的鉴定体系。选取13个微卫星基因座作为标记,采集了53头德州驴血液样本,其中子代驴驹16头,候选父本13头,候选母本24头,用酚-仿法抽提血液基因组进行PCR扩增和基因扫描,并利用Peak Scanner Software v1.0软件读取基因型分型结果。对微卫星基因座的遗传多样性进行分析,利用似然法（Cervus 3.0软件）和排除法对个体间的亲子关系进行了鉴定。结果显示,13个微卫星基因座的平均等位基因数、平均观测杂合度（Ho）、平均期望杂合度（He）和平均多态信息含量（PIC）分别为6.846、0.689、0.671和0.625。期望杂合度与观测杂合度之差在0.002~0.088之间,差值较小。13个微卫星基因座的累计排除概率（EP）达到0.990以上。微卫星基因座具有高度多态性和较高的排除概率,适用于遗传分析和个体鉴定。利用Cervus 3.0软件基于似然法分析得到了16头子代驴驹的最似亲本,结合排除法对这16头驴驹及其最似亲本进行基因型比对,最终在53头德州驴中确定了11个亲子对。本试验建立了以13个微卫星位点作为核心标记,将似然法和排除法相结合作为主要分析方法的德州驴亲子关系鉴定体系,为育种工作提供参考资料。     

四川常羽乌骨鸡群体遗传多样性分析

利用选自家禽基因组的10个微卫星标记,对四川常羽乌骨鸡5个群体(四川山地乌骨鸡白羽系、黑羽系;黄忠山地乌骨鸡;黄忠山地乌骨鸡绿壳蛋系;草科乌骨鸡)的遗传多样性进行了检测,计算了各群体的群体杂合度、群体间遗传距离,并根据遗传距离进行了聚类分析。结果表明所选择的微卫星标记在各群体中表现出较高的多态性;四川5个乌骨鸡群体遗传多样性比较丰富,群体平均杂合度为0.5383到0.6659;各群体间的遗传距离有一定的差异;聚类分析将5个群体聚为三类。     

Parentage assignment with genotyping‐by‐sequencing data

In this paper, we evaluate using genotype‐by‐sequencing (GBS) data to perform parentage assignment in lieu of traditional array data. The use of GBS data raises two issues: First, for low‐coverage (e.g., <2×) GBS data, it may not be possible to call the genotype at many loci, a critical first step for detecting opposing homozygous markers. Second, the amount of sequencing coverage may vary across individuals, making it challenging to directly compare the likelihood scores between putative parents. To address these issues, we extend the probabilistic framework of Huisman (Molecular Ecology Resources, 2017, 17, 1009) and evaluate putative parents by comparing their (potentially noisy) genotypes to a series of proposal distributions. These distributions describe the expected genotype probabilities for the relatives of an individual. We assign putative parents as a parent if they are classified as a parent (as opposed to e.g., an unrelated individual), and if the assignment score passes a threshold. We evaluated this method on simulated data and found that (a) high‐coverage (>2×) GBS data performs similarly to array data and requires only a small number of markers to correctly assign parents and (b) low‐coverage GBS data (as low as 0.1×) can also be used, provided that it is obtained across a large number of markers. When analysing the low‐coverage GBS data, we also found a high number of false positives if the true parent is not contained within the list of candidate parents, but that this false positive rate can be greatly reduced by hand tuning the assignment threshold. We provide this parentage assignment method as a standalone program called AlphaAssign.     

Association of a single nucleotide polymorphism in SPP1 with growth traits and twinning in a cattle population selected for twinning rate

Continued validation of genetic markers for economically important traits is crucial to establishing marker-assisted selection as a tool in the cattle industry. The objective of the current study was to evaluate the association of a SNP (T(9)/T(10)) in the osteopontin gene (SPP1) with growth rate in a large cattle population spanning multiple generations and representing alleles from 12 founding breeds. This population has been maintained at the US Meat Animal Research Center since 1981 and subjected to selection for twinning rate. Phenotypic records for this population included twinning rate and ovulation rate, providing an opportunity to examine the potential effects of SPP1 genotype on reproductive traits. A set of 2,701 animals was geno-typed for the T(9)/T(10) polymorphism at SPP1. The geno-typic data, including previously genotyped markers on chromosome 6 (BTA6), were used in conjunction with pedigree information to estimate genotypic probabilities for all 14,714 animals with phenotypic records. The genotypic probabilities for females were used to calculate independent variables for regressions of additive, dominance, and imprinting effects. Genotypic regressions were fit as fixed effects in a mixed model analysis, in which each trait was analyzed in a 2-trait model where single births were treated as a separate trait from twin births. The association of the SPP1 marker with birth weight (P < 0.006), weaning weight (P < 0.007), and yearling weight (P < 0.003) was consistent with the previously reported effects of SPP1 genotype on yearling weight. Our data supports the conclusion that the SNP successfully tracks functional alleles affecting growth in cattle. The previously undetected effect of the SNP on birth and weaning weight suggests this particular SPP1 marker may explain a portion of the phenotypic variance explained by QTL for birth and HCW on BTA6.     

西北地区和尚头小麦遗传多样性及农艺性状的关联分析

为了解西北地区和尚头小麦种质资源的遗传特性及主要农艺性状特征,采用43份不同来源的和尚头小麦种质材料,在均匀分布于小麦21条染色体上的150个SSR(simple sequence repeats)位点上检测遗传多样性,同时对19个农艺性状在两个试验点进行表型鉴定,并采用GLM(general linear model)模型进行分子标记与表型性状的关联分析。结果表明,19个农艺性状中数量性状遗传多样性明显高于质量性状,除壳色外,其他性状之间均存在不同程度的相关性。利用45对具有多态性的SSR标记共检测出151个等位变异,各标记等位位点变化范围为2～6,平均为3.36个,PIC(polymorphism information content)值变异范围为0.044～0.771。群体遗传结构分析将43份材料划分为8个亚群。关联分析发现11个SSR标记与农艺性状显著关联,单个标记对表型变异的解释率为8.89%～24.74%,这些标记可为特色小麦分子标记辅助选择育种提供理论参考。     

长江三角洲白山羊群体遗传结构研究

应用结构基因座和微卫星DNA两种遗传标记探讨长江三角洲白山羊群体遗传结构。结果表明,检测的9个结构基因座位上7个存在多态性,座位的基因平均杂合度、多态信息含量及有效等位基因数分别为0.1767、0.1457和1.2837;7个微卫星位点上共检测到110个等位基因,位点的基因平均杂合度、多态信息含量及有效等位基因数分别为0.8867、0.8774和11.2907。群体内的遗传变异程度相对较高,反映出丰富的遗传多样性,而且微卫星DNA标记揭示的遗传变异高于结构基因座。     

拉布拉多犬的毛色遗传和繁殖选育

本文通过对影响犬被毛颜色色度的不同类型的黑色素,以及控制色素沉着的等位基因位点的深入分析探讨,了解和掌握拉犬毛色的表现型和基因型,以及B、b、E和e等位基因的遗传知识,就可以尝试利用谱系和后代的毛色信息确定父母本的毛色基因型,可以对拉犬的毛色进行所希望的繁殖选育,并可以预测后代中所有被毛颜色出现的比例。通过对色素修饰基因的分析探讨,了解和色素拉犬毛色的独特变化。