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1.
Genetic diversity in the Dutch Landrace goat was investigated based on information from the pedigree with about 6500 animals. Annual inbreeding rate after 1985 was below 0.5% and after 1987 close to 0%. However, pedigree information was incomplete, and 350 animals had unknown parents, while for the majority the real parents must have been in the pedigree. To determine the influence of unknown parents, 20 new pedigrees were created by random assignment of animals, alive at the time of birth, as parents to individuals with unknown parents. Only 12 founders remained for these pedigrees, and inbreeding levels varied considerably between these 20 pedigrees. However, inbreeding rates were remarkably constant. They increased to about 0.2%, indicating that the population is not endangered by inbreeding. The optimal contribution theory was used to evaluate possibilities of decreasing the average relationship in the population and thus to increase the genetic diversity of the breed. Optimal contribution decreased the average relationship in the population whether randomly assigned parents were used or not. However, individuals selected as parents for the resampled pedigrees differed from the original pedigree, and only a few animals were selected for all pedigrees. Candidates for inclusion in the genebank were also selected using optimal contribution. Adding animals to the genebank increased the conserved genetic diversity substantially, but as the lists differed between the analysed pedigrees it was not clear which animals were best added to the genebank.  相似文献   

2.
Boran cattle provide livelihood to thousands of households in the arid and semiarid lands of Kenya. Due to their superior adaptive and productive traits in comparison to other breeds of cattle, they have also become a popular choice for breeders in Eastern and Southern Africa. Continued genetic improvement of the breed is important, and therefore accurate performance and pedigree records are required. One hundred seventy-eight pedigree records and blood samples of four Boran stud herds were evaluated for accuracy of parentage allocation using 11 microsatellite markers recommended by ISAG for parentage verification. The panel of the 11 microsatellite markers was found to be highly polymorphic (PIC of 0.6901) with a combined probability of exclusion of 0.9997. The dam misidentification was low ranging between 0% and 5% for the herds tested. The estimated rate of mispaternity however ranged between 4.3% and 80% among the four stud herds, and more than 50% of the offspring of some herds were misidentified. The high rate of mispaternity will have a negative impact on the response to selection. The use of DNA markers for parentage assignment will improve the accuracy of the pedigree records of Boran stud cattle in Kenya and contribute to more accurate selection of superior animals.  相似文献   

3.
Markers flanking DNA regions, where quantitative trait loci (QTL) have been previously spotted, can be used to trace the common inheritance of major genes for a better definition of covariances among animals. A practical approach to the use of marker data to refine the additive relationship matrix used in the traditional best linear unbiased prediction (BLUP) methodology is presented. The technique allows the number of the mixed model equations to be kept to an animal level, blending polygenic pedigree data with marker haplotype information. The advantage of this marker-assisted selection (MAS) approach over BLUP selection has been assessed through a stochastic simulation. A finite locus model with 32 independent biallelic loci was generated with normally distributed allelic effects. The heritability of the trait, measured on both sexes and on females only, was set to 0.2 and 0.5. Five-allelic markers 2, 10 and 20 cM apart, bracketed the QTL with the largest effect on the trait, accounting for 17% of the genetic variance. The bracketed QTL had two or eight alleles and its position was undefined within the bracket. Results show a moderate 2% advantage of MAS over BLUP in terms of higher genetic response when trait was recorded on both sexes and heritability was 0.2. The benefit is in the short term, but it lasts longer with polyallelic QTL. When the trait was recorded on females only, MAS produced only a small and insignificant genetic gain, but reduced the overall inbreeding in the population. MAS was also inefficient when heritability was 0.5.  相似文献   

4.
利用微卫星标记鉴定德州驴亲子关系   总被引：1，自引：1，他引：0  
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。  相似文献   

5.
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.  相似文献   

6.
Deoxyribonucleic acid-based tests were used to assign paternity to 625 calves from a multiple-sire breeding pasture. There was a large variability in calf output and a large proportion of young bulls that did not sire any offspring. Five of 27 herd sires produced over 50% of the calves, whereas 10 sires produced no progeny and 9 of these were yearling bulls. A comparison was made between the paternity results obtained when using a DNA marker panel with a high (0.999), cumulative parentage exclusion probability (P(E)) and those obtained when using a marker panel with a lower P(E) (0.956). A large percentage (67%) of the calves had multiple qualifying sires when using the lower resolution panel. Assignment of the most probable sire using a likelihood-based method based on genotypic information resolved this problem in approximately 80% of the cases, resulting in 75% agreement between the 2 marker panels. The correlation between weaning weight, on-farm EPD based on pedigrees inferred from the 2 marker panels was 0.94 for the 24 bulls that sired progeny. Partial progeny assignments inferred from the lower resolution panel resulted in the generation of EPD for bulls that actually sired no progeny according to the high-P(E) panel, although the Beef Improvement Federation accuracies of EPD for these bulls were never greater than 0.14. Simulations were performed to model the effect of loci number, minor allele frequency, and the number of offspring per bull on the accuracy of genetic evaluations based on parentage determinations derived from SNP marker panels. The SNP marker panels of 36 and 40 loci produced EPD with accuracies nearly identical to those EPD resulting from use of the true pedigree. However, in field situations where factors including variable calf output per sire, large sire cohorts, relatedness among sires, low minor allele frequencies, and missing data can occur concurrently, the use of marker panels with a larger number of SNP loci will be required to obtain accurate on-farm EPD.  相似文献   

7.
Some individual genetic markers show strong and apparently consistent effects on trait merit and are taken as causative mutations that can be used directly as fixed effects in marker‐assisted selection programs. If the effect of such a marker is seen to decrease over time, key reasons include epistasis, where the effect depends on genetic background, and recombination, where the marker is in fact not causative, and strong linkage disequilibrium between the marker and the causative QTL is breaking down. This paper presents a method to detect the latter scenario, including calculation of the probability of a recombinant haplotype for each gamete contributing to each individual in a pedigree. This method requires only pedigree, phenotypes and genotypic information on the single marker. Missing marker genotypes are handled by the method, but with diminishing power. For biallelic markers, strong QTL effects are needed for the method to be of clear value. Given suitable results, breeders may chose to eliminate certain individuals from the breeding program in order to continue using the single genetic marker under high linkage disequilibrium with the causative QTL. Alternatively, other linked markers might be sought that can be used individually or in haplotype tests to restore strong LD for marker‐assisted selection.  相似文献   

8.
对于数量性状能否作基因定位的问题,过去认为这是不可能的。因为数量性状是受微效多基因决定。而这些基因的数目和单独效应又很难确定。下面刊出的李玉奎和吴常信两位先生撰写的《RFLP在动物育种中应用的前景》一文对这一问题的解决介绍了可供研究的途径。  相似文献   

9.
牦牛DNA分子遗传标记的研究   总被引：2，自引：0，他引：2  
本文在归纳总结DNA分子遗传标记的类型、特点和检出方式的基础上,分析讨论了动物遗传育种研究中常用的DNA分子遗传标记如RFLP标记、VNTR标记、AFLP标记、PCR-SSCP标记、RAPD标记、SNPs标记、微卫星标记、DNA指纹标记及mtDNA标记等在牦牛遗传育种研究中的研究现状和存在的问题,指出DNA分子标记在牦牛遗传育种研究中已渗透到牦牛品种的起源、演化和分类研究;牦牛品种间或品种内个体间以及与其他种间亲缘关系鉴定;犏牛雄性不育的机理研究及牦牛经济性状功能基因的克隆和多态性研究等方面。最后探讨了今后的研究趋势和发展前景。  相似文献   

10.
The reliability of genomic evaluations depends on the proportion of genetic variation explained by the DNA markers. In this study, we have estimated the proportion of variance in daughter trait deviations (DTDs) of dairy bulls explained by 45 993 genome wide single‐nucleotide poly‐ morphism (SNP) markers for 29 traits in Australian Holstein‐Friesian dairy cattle. We compare these proportions to the proportion of variance in DTDs explained by the additive relationship matrix derived from the pedigree, as well as the sum of variance explained by both pedigree and marker information when these were fitted simultaneously. The propor‐ tion of genetic variance in DTDs relative to the total genetic variance (the total genetic variance explained by the genomic relationships and pedigree relationships when both were fitted simultaneously) varied from 32% for fertility to approximately 80% for milk yield traits. When fitting genomic and pedigree relationships simultaneously, the variance unexplained (i.e. the residual variance) in DTDs of the total variance for most traits was reduced compared to fitting either individually, suggesting that there is not complete overlap between the effects. The proportion of genetic variance accounted by the genomic relationships can be used to modify the blending equations used to calculate genomic estimated breeding value (GEBV) from direct genomic breeding value (DGV) and parent average. Our results, from a validation population of young dairy bulls with DTD, suggest that this modification can improve the reliability of GEBV by up to 5%.  相似文献   

11.
A population of Baudet du Poitou donkeys was genetically characterized using microsatellites. The results were used to verify the pedigrees and to estimate the genetic variability. It could be confirmed that a equine parentage test kit works well for donkeys and that by using 13 microsatellites more than 99% of wrong pedigree informations would be detected. The genetic variability was comparable to a representative group of Baudet du Poitou donkeys in France.  相似文献   

12.
本研究旨在利用SNP标记对北京地区中国荷斯坦牛群进行亲子推断,并分析场、母牛出生年月、公牛家系对系谱错误率的影响,以期为指导奶牛育种和生产管理提供依据。共选取了255个最小等位基因频率大于0.45的高多态SNPs标记,利用似然法,采用Cervus3.0软件对北京地区84头荷斯坦公牛和1 927头母牛进行亲子推断研究。结果显示,试验群体平均系谱错误率为20.9%,不同的场、出生年份和月份的母牛的系谱错误率有显著差异(P<0.05),而各公牛家系间系谱错误率差异不显著(P>0.05)。结果说明,错误系谱的发生主要是由于牛场本身记录不完善造成的。在我国亟需建立利用遗传标记监测、校正系谱准确性的制度,采取措施提高系谱的准确性,加快我国荷斯坦牛遗传改良进程。  相似文献   

13.
Joint Nordic (Denmark, Finland, Sweden) genetic evaluation of female fertility is currently based on the multiple trait multilactation animal model (BLUP). Here, single step genomic model (ssGBLUP) was applied for the Nordic Red dairy cattle fertility evaluation. The 11 traits comprised of nonreturn rate and days from first to last insemination in heifers and first three parities, and days from calving to first insemination in the first three parities. Traits had low heritabilities (0.015–0.04), but moderately high genetic correlations between the parities (0.60–0.88). Phenotypic data included 4,226,715 animals with records and pedigree 5,445,392 animals. Unknown parents were assigned into 332 phantom parent groups (PPG). In mixed model equations animals were associated with PPG effects through the pedigree or both the pedigree and genomic information. Genotype information of 46,914 SNPs was available for 33,969 animals in the pedigree. When PPG used pedigree information only, BLUP converged after 2,420 iterations whereas the ssGBLUP evaluation needed over ten thousand iterations. When the PPG effects were solved accounting both the pedigree and the genomic information, the ssGBLUP model converged after 2,406 iterations. Also, with the latter model breeding values by ssGBLUP and BLUP became more consistent and genetic trends followed each other well. Models were validated using forward prediction of the young bulls. Reliabilities and variance inflation of predicted genomic breeding values (values for parent averages in brackets) for the 11 traits ranged 0.22–0.31 (0.10–0.27) and 0.81–0.95 (0.83–1.06), respectively. The ssGBLUP model gave always higher validation reliabilities than BLUP, but largest increases were for the cow fertility traits.  相似文献   

14.
Estimated breeding value (EBV) was calculated based on either individual phenotype (SP), an index of individual phenotype and full- and half-sib family averages (SI) or Best Linear Unbiased Prediction (BLUP). Calculations were done with correct data or data with 5, 10, 15 or 20% of the records per generation containing pedigree errors. Traits considered were litter size (LS), backfat (BF) and average daily gain (ADG). When data were correct, BLUP resulted in an advantage in expected genetic gain over SP of 22, 7.2 or 30.8% for LS, BF and ADG, respectively, and over SI of 9.6, 3.8 or 21.4%. When sire and dam pedigrees were incorrect for 20% of the pigs each generation, genetic gain using SI was reduced by 7, 2.5 or 6.5% and genetic gain using BLUP was reduced by 9.3, 3.2 or 12.4% for LS, BF and ADG, respectively. With 20% of the pedigrees in error, the advantages in genetic gain of using BLUP over SP, the method unaffected by errors in pedigree, were 10.5, 3.8 and 14.6% for LS, BF and ADG, respectively. These results suggest that, although BLUP is affected to a greater degree by pedigree errors than SP or SI, selection of swine using BLUP still would improve response to selection over the use of SP or SI.  相似文献   

15.
Genetic marker data are likely to be obtained from a relatively small proportion of the individuals in many livestock populations. Information from genetic markers can be extrapolated to related individuals without marker data by computing genotype probabilities using an algorithm referred to as peeling. However, genetic markers may have many alleles and the number of computations in traditional peeling algorithms is proportional to the number of alleles raised to the sixth or eighth power, depending on pedigree structure. An alternative algorithm for computing genotype probabilities of marker loci with many alleles in large, nonlooped pedigrees with incomplete marker data is presented. The algorithm is based on recursive computations depending on alleles instead of genotypes, as in traditional peeling algorithms. The number of computations in the allelic peeling algorithm presented here is proportional to the square of the number of alleles, which makes this algorithm more computationally efficient than traditional peeling for loci with many alleles. Memory requirements are roughly proportional to the number of individuals in the pedigree and the number of alleles. The recursive allelic peeling algorithm cannot be applied to pedigrees that include full sibs or loops. However, it is a preliminary step toward a more complex and encompassing iterative approach to be described in a companion paper.  相似文献   

16.
Traditional breeding programmes have largely contributed to disseminate the benefits of several quantitative traits in livestock. In developing countries such as Indonesia where animal population scattered throughout the country, it is difficult to invest for molecular research. On the other side, yet, it is worthy asset for breeding purposes. Based on theory and evidence, it has been proved that those scattered population evolved different genetic adaptations in response to a given natural pressure selection. A global strategy can be applied to the use of molecular genetic information for identification of economically important value. The use of genetic markers or more effective of marker-assisted selection (MAS) for desired important traits would be more valuable and useful and even more efficient in important trait selection of superior livestock. DNA marker technology would be very useful when applied for quantitative trait identification. Marker-assisted selection can be used for enhancing conventional breeding and works best for the traits with low heritability such as in reproductive traits and disease resistance. Application of conventional breeding for lower heredity traits would not be efficient because of waiting longer for generation interval, expensive in measurements, more population and more employees needed. Study of quantitative trait loci mapping is early investment to improve genetic merit. It can be performed once but can be used for exploring many genetic traits with economically important values. An effective option is biotechnology application in livestock for the development of genetic varieties such as stress tolerance, growth and carcass traits. Application of biotechnology approaches will enable improvement in productivity, reduction in costs, enrichment of milk compositions and extension of shelf life products.  相似文献   

17.
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.  相似文献   

18.
This study investigated, through stochastic computer simulation, the extra gains expected from marker-assisted selection (MAS) in an infinitesimal model with linkage. The trait under selection was assumed to be controlled by 2,000 loci of additive small effect and evenly distributed in c chromosomes of one Morgan each (and c = 5, 10, 20, or 30). This approach differs from previous studies on the benefits of MAS that have considered mixed inheritance models. Marker information was used together with pedigree information to compute the relationship matrix used in BLUP genetic evaluations. The MAS schemes were compared with schemes where genetic evaluations were performed using standard BLUP (i.e., the relationship matrix is obtained using pedigree information only). When the number of markers was large enough (approximately one marker every 10 cM), there were increases in the accuracy of selection with MAS, and this led to extra gains compared with standard BLUP for all genome sizes considered. The benefit from MAS increased over generations. At the last generation of selection (Generation 10), the response from MAS was 11, 9, 7, and 5% greater than with standard BLUP for genomes with 5, 10, 20, and 30 chromosomes, respectively. Thus, although small, gains from MAS were nonetheless detectable for genome sizes typical of livestock populations.  相似文献   

19.
The selection of genetically superior individuals is conditional upon accurate breeding value predictions which, in turn, are highly depend on how precisely relationship is represented by pedigree. For that purpose, the numerator relationship matrix is essential as a priori information in mixed model equations. The presence of pedigree errors and/or the lack of relationship information affect the genetic gain because it reduces the correlation between the true and estimated breeding values. Thus, this study aimed to evaluate the effects of correcting the pedigree relationships using single‐nucleotide polymorphism (SNP) markers on genetic evaluation accuracies for resistance of beef cattle to ticks. Tick count data from Hereford and Braford cattle breeds were used as phenotype. Genotyping was carried out using a high‐density panel (BovineHD ‐ Illumina® bead chip with 777 962 SNPs) for sires and the Illumina BovineSNP50 panel (54 609 SNPs) for their progenies. The relationship between the parents and progenies of genotyped animals was evaluated, and mismatches were based on the Mendelian conflicts counts. Variance components and genetic parameters estimates were obtained using a Bayesian approach via Gibbs sampling, and the breeding values were predicted assuming a repeatability model. A total of 460 corrections in relationship definitions were made (Table 1) corresponding to 1018 (9.5%) tick count records. Among these changes, 97.17% (447) were related to the sire's information, and 2.8% (13) were related to the dam's information. We observed 27.2% (236/868) of Mendelian conflicts for sire–progeny genotyped pairs and 14.3% (13/91) for dam–progeny genotyped pairs. We performed 2174 new definitions of half‐siblings according to the correlation coefficient between the coancestry and molecular coancestry matrices. It was observed that higher‐quality genetic relationships did not result in significant differences of variance components estimates; however, they resulted in more accurate breeding values predictions. Using SNPs to assess conflicts between parents and progenies increases certainty in relationships and consequently the accuracy of breeding value predictions of candidate animals for selection. Thus, higher genetic gains are expected when compared to the traditional non‐corrected relationship matrix.  相似文献   

20.
Reliability of parentage test panels is usually based on its power to exclude wrong parentage assignments based on allele frequencies. We evaluated the rates of false exclusions and inclusions in parentage assignments, and how these results are affected by allele frequencies, panel sizes and the number of allowed mismatches. We also evaluated the reliability of parentage testing by comparing populations with distinct genetic backgrounds using pure and composite families of cattle and sheep. Allowing for 1% genotype mismatches in true parent–offspring relations provided the best compromise between false‐positive and false‐negative assignments. Pure breeds needed at least 200–210 single‐nucleotide polymorphism (SNP) markers to correctly assign relations, but between 700 and 890 markers to avoid assigning incorrect relationships. Composite breeds needed between 220 (sheep) and 500 (cattle) markers for correct assignment; 680 (cattle) to 4400 (sheep) SNPs were needed to eliminate false‐positive assignments. Allowing 0% genotype mismatches decreased false‐positive but increased false‐negative assignments, whilst a higher threshold of 2% showed the opposite effects. Panels with high minor allele frequencies (0.35–0.45) provided the best chance for correct parentage resolutions requiring fewer markers. Further, we propose that a dynamic threshold would allow adapting to population specific error rates. A comparison to the performance of the official International Society for Animal Genetics SNP panel for cattle and a recently published SNP panel for sheep showed that randomly selected markers performed only slightly worse for the applied parentage test based on opposing homozygotes. This suggests that even with carefully selected panels, only marginal assignment improvements are obtainable for a particular number of SNPs. The main point for improvement is the number of markers used. We recommend using at least 200 SNP markers for parentage testing if the aim is to reduce false‐negative results. To fully exclude false positives at least 700 markers are required.  相似文献   

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