共查询到18条相似文献，搜索用时 328 毫秒
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[目的]为QTL定位中进一步估计QTL的位置和影响效应提供必要的依据。[方法]以BC1设计为资源群体,通过计算机模拟研究了不同群体规模、标记-QTL间图距、性状遗传力和QTL效应（QTL方差占加性遗传方差的比例）对单标记分析检测QTL效率的影响。[结果]表明：资源群体规模较大,标记与QTL的间距较小（或标记与QTL连锁紧密）,目标性状的遗传力较高,且QTL效应较大时,采用单标记分析方法检测QTL的检出率较高。当所检测的标记距离QTL较近时,获得相同的QTL检出率所需的资源群体规模更小。[结论]QTL效应对QTL检出率的影响会受性状遗传力的制约,如果性状的遗传力过低,即使QTL方差占遗传方差的比例很高,也很难获得理想的QTL检出率。 相似文献
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本研究旨在对比值性状QTL采用贝叶斯定位方法进行探讨。将两个具有正态分布的普通数量性状之比定义为比值性状。由于此类性状不服从正态分布,因此在遗传分析上不同于普通性状。利用构成比值性状的两个组分性状的线性结合,我们提出了定位比值性状数量性状位点(QTL)的最大似然法。在此基础上,进一步探索比值性状的贝叶斯定位策略。首先采用贝叶斯压缩方法估计两个组分性状的QTL参数,然后利用两个组分性状的群体均值和QTL遗传效应,产生一个关于比值性状QTL遗传效应的后验样本,通过对这个后验样本的统计分析,来推断比值性状的QTL。模拟研究表明:新方法表现出比似然法更高的QTL检测效力。 相似文献
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本研究针对猪育种中重点考虑的窝产活仔猪数（NBA）、达100 kg体重日增重（ADG）、饲料利用率（FCR）、达100 kg体重的背膘厚（BF）、肌内脂肪含量（IMF） 5个性状,利用连锁平衡（linkage equilibrium,LE）、连锁不平衡（linkage disequilibrium,LD）标记和直接标记（direct marker,DR）3种类型的分子遗传标记,设计了3个规模不同的基础群,母猪数分别为100、200、300头,公猪数都为10头,基础群个体间无亲缘关系,育种群实施闭锁繁育。用Monte Carlo方法模拟了MAS的5个世代选择试验。育种值估计采用标准BLUP（Standard BLUP,SBLUP）模型（此育种值作为对照）、QBLUP模型（使用DR标记）、MBLUP模型（使用LD和LE标记）。结果表明,利用DR标记在各种情况下都比利用LD和LE标记获得的选择效率高;5个性状中,MAS对低遗传力、限性性状NBA的选择效率最高;当性状的QTL方差占遗传方差基本相同时,中等遗传力性状FCR的选择效率比高遗传力性状BF的更高;当性状的遗传力差异不大时,QTL方差占遗传方差比例大的性状FCR的选择效率比QTL方差占遗传方差比例小的性状ADG的更高。当利用QBLUP模型时,MAS对NBA的选择效率最高,ADG的选择效率最低。 相似文献
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采用Ｍｏｎｔｅ Ｃａｒｌｏ模拟方法，研究了家系数目，家系大小，性状遗传力大小等３个因素在不同组合下，ＭＬ法和ＲＥＭＬ法方差组分估计的准确性。结果表明，在不考虑除均值之外其它固定效应的情况下，ＭＬ法的效率高于ＲＥＭＬ法。 相似文献
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性别效应对家蚕茧质性状QTL定位的影响 总被引：1，自引：0，他引：1
家蚕茧质性状的性别效应十分明显。分别以性别效应调整前和调整后的家蚕全茧量、茧层量、茧层率和蛹体质量等数量性状值为基础,对性别效应调整前后的茧质性状作数量性状基因座(QTL)定位比较分析,以探讨性别效应对家蚕QTL定位的影响。结果显示,检测出的控制各性状的上位性位点数、QTL总数以及效应显著的QTL数等,都表现为调整前比调整后要多,有效QTL在连锁群上的分布也表现一定的差异。此结果说明由于性别效应的影响可能会导致检测出控制家蚕茧质性状的上位性位点数和QTL总数的增加及其分布的不同,从而引起QTL分析结果的偏差。 相似文献
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不同标记数对家蚕茧质性状的QTL定位比较 总被引：2，自引：1，他引：1
分析了家蚕茧质性状不同标记数的QTL定位效果 :6 92个标记和 5 4 2个标记的全茧量都是以基因互作效应为主 ,而茧层量、茧层率以及蛹体重性状既有加性也有显性和互作效应 ,且与全茧量、茧层量、茧层率和蛹体重之间的基本相关性相吻合 ;392个标记的分析结果与前两种类型有别 ,定位的总QTL组合数、QTL总数 ,以及效应显著的QTL数都表现最多 ,表明标记数减少反而定位出更多的QTL ,但 392个标记定位的QTL在连锁群的分布同全茧量与蛹体重、茧层量与茧层率之间的显著正相关不符合。分析认为 6 92个标记数的定位结果比较可靠。QTL的效应与贡献率之间的关系分析结果显示 :QTL效应值与QTL贡献率的相关系数达 0 95以上 ,表现为显著的正相关关系 ;但QTL的效应值和贡献率的大小与QTL效应的显著性并无直接关系。 相似文献
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Generalized marker regression and interval QTL mapping methods for binary traits in half-sib family designs 总被引：3，自引：0，他引：3
H. N. Kadarmideen & J. C. M. Dekkers 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2001,118(5):297-309
A Generalized Marker Regression Mapping (GMR) approach was developed for mapping Quantitative Trait Loci (QTL) affecting binary polygenic traits in a single-family half-sib design. The GMR is based on threshold-liability model theory and regression of offspring phenotype on expected marker genotypes at flanking marker loci. Using simulation, statistical power and bias of QTL mapping for binary traits by GMR was compared with full QTL interval mapping based on a threshold model (GIM) and with a linear marker regression mapping method (LMR). Empirical significance threshold values, power and estimates of QTL location and effect were identical for GIM and GMR when QTL mapping was restricted to within the marker interval. These results show that the theory of the marker regression method for QTL mapping is also applicable to binary traits and possibly for traits with other non-normal distributions. The linear and threshold models based on marker regression (LMR and GMR) also resulted in similar estimates and power for large progeny group sizes, indicating that LMR can be used for binary data for balanced designs with large families, as this method is computationally simpler than GMR. GMR may have a greater potential than LMR for QTL mapping for binary traits in complex situations such as QTL mapping with complex pedigrees, random models and models with interactions. 相似文献
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Yang B Navarro N Noguera JL Muñoz M Guo TF Yang KX Ma JW Folch JM Huang LS Pérez-Enciso M 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2011,128(5):329-343
Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits. 相似文献
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The effectiveness of five selection methods for genetic improvement of net merit comprising trait 1 of low heritability (h2 = 0.1) and trait 2 of high heritability (h2 = 0.4) was examined: (i) two‐trait quantitative trait loci (QTL)‐assisted selection; (ii) partial QTL‐assisted selection based on trait 1; (iii) partial QTL‐assisted selection based on trait 2; (iv) QTL‐only selection; and (v) conventional selection index without QTL information. These selection methods were compared under 72 scenarios with different combinations of the relative economic weights, the genetic correlations between traits, the ratio of QTL variance to total genetic variance of the trait, and the ratio of genetic variances between traits. The results suggest that the detection of QTL for multiple‐trait QTL‐assisted selection is more important when the index traits are negatively correlated than when they are positively correlated. In contrast to literature reports that single‐trait marker‐assisted selection (MAS) is the most efficient for low heritability traits, this study found that the identified QTL of the low heritability trait contributed negligibly to total response in net merit. This is because multiple‐trait QTL‐assisted selection is designed to maximize total net merit rather than the genetic response of the individual index trait as in the case of single‐trait MAS. Therefore, it is not economical to identify the QTL of the low heritability traits for the improvement of total net merit. The efficient, cost‐effective selection strategy is to identify the QTL of the moderate or high heritability traits of the QTL‐assisted selection index to facilitate total economic returns. Detection of the QTL of the low h2 traits for the QTL‐assisted index selection is justified when the low h2 traits have high negative genetic correlation with the other index traits and/or when both economic weights and genetic variances of the low h2 traits are larger as compared to the other index traits of higher h2. This study deals with theoretical efficiency of QTL‐assisted selection, but the same principle applies to SNP‐based genomic selection when the proportion of the genetic variance ‘explained by the identified QTLs’ in this study is replaced by ‘explained by SNPs’. 相似文献
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Sherman EL Nkrumah JD Li C Bartusiak R Murdoch B Moore SS 《Journal of animal science》2009,87(1):37-45
Feed intake and feed efficiency are economically important traits in beef cattle because feed is the greatest variable cost in production. Feed efficiency can be measured as feed conversion ratio (FCR, intake per unit gain) or residual feed intake (RFI, measured as DMI corrected for BW and growth rate, and sometimes a measure of body composition, usually carcass fatness, RFI(bf)). The goal of this study was to fine map QTL for these traits in beef cattle using 2,194 markers on 24 autosomes. The animals used were from 20 half-sib families originating from Angus, Charolais, and University of Alberta Hybrid bulls. A mixed model with random sire and fixed QTL effect nested within sire was used to test each location (cM) along the chromosomes. Threshold levels were determined at the chromosome and genome levels using 20,000 permutations. In total, 4 QTL exceeded the genome-wise threshold of P < 0.001, 3 exceeded at P < 0.01, 17 at P < 0.05, and 30 achieved significance at the chromosome-wise threshold level (at least P < 0.05). No QTL were detected on BTA 8, 16, and 27 above the 5% chromosome-wise significance threshold for any of the traits. Nineteen chromosomes contained RFI QTL significant at the chromosome-wise level. The RFI(bf) QTL results were generally similar to those of RFI, the positions being similar, but occasionally differing in the level of significance. Compared with RFI, fewer QTL were detected for both FCR and DMI, 12 and 4 QTL, respectively, at the genome-wise thresholds. Some chromosomes contained FCR QTL, but not RFI QTL, but all DMI QTL were on chromosomes where RFI QTL were detected. The most significant QTL for RFI was located on BTA 3 at 82 cM (P = 7.60 x 10(-5)), for FCR on BTA 24 at 59 cM (P = 0.0002), and for DMI on BTA 7 at 54 cM (P = 1.38 x 10(-5)). The RFI QTL that showed the most consistent results with previous RFI QTL mapping studies were on BTA 1, 7, 18, and 19. The identification of these QTL provides a starting point to identify genes affecting feed intake and efficiency for use in marker-assisted selection and management. 相似文献
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旨在探究快速型黄羽肉鸡饲料利用效率性状的遗传参数,评估不同方法所得估计育种值的准确性。本研究以自主培育的快速型黄羽肉鸡E系1 923个个体（其中公鸡1 199只,母鸡724只）为研究素材,采用"京芯一号"鸡55K SNP芯片进行基因分型。分别利用传统最佳线性无偏预测（BLUP）、基因组最佳线性无偏预测（GBLUP）和一步法（SSGBLUP）3种方法,基于加性效应模型进行遗传参数估计,通过10倍交叉验证比较3种方法所得估计育种值的准确性。研究性状包括4个生长性状和4个饲料利用效率性状：42日龄体重（BW42D）、56日龄体重（BW56D）、日均增重（ADG）、日均采食量（ADFI）和饲料转化率（FCR）、剩余采食量（RFI）、剩余增长体重（RG）、剩余采食和增长体重（RIG）。结果显示,4个饲料利用效率性状均为低遗传力（0.08~0.20）,其他生长性状为中等偏低遗传力（0.11~0.35）;4个饲料利用效率性状间均为高度遗传相关,RFI、RIG与ADFI间为中度遗传相关,RFI与ADG间无显著相关性,RIG与ADG间为低度遗传相关。本研究在获得SSGBLUP方法的最佳基因型和系谱矩阵权重比基础上,比较8个性状的估计育种值准确性,SSGBLUP方法获得的准确性分别比传统BLUP和GBLUP方法提高3.85%~14.43%和5.21%~17.89%。综上,以RIG为选择指标能够在降低日均采食量的同时保持日均增重,比RFI更适合快速型黄羽肉鸡的选育目标;采用最佳权重比进行SSGBLUP分析,对目标性状估计育种值的预测性能最优,建议作为快速型黄羽肉鸡基因组选择方法。 相似文献
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The effect on power and precision of including the causative SNP amongst the investigated markers in Quantitative Trait Loci (QTL) mapping experiments was investigated. Three fine mapping methods were tested to see which was most efficient in finding the causative mutation: combined linkage and linkage disequilibrium mapping (LLD); association mapping (MARK); a combination of LLD and association mapping (LLDMARK). Two simulated data sets were analysed: in one set, the causative SNP was included amongst the markers, while in the other set the causative SNP was masked between markers. Including the causative SNP amongst the markers increased both precision and power in the analyses. For the LLD method the number of correctly positioned QTL increased from 17 for the analysis without the causative SNP to 77 for the analysis including the causative SNP. The likelihood of the data analysis increased from 3.4 to 13.3 likelihood units for the MARK method when the causative SNP was included. When the causative SNP was masked between the analysed markers, the LLD method was most efficient in detecting the correct QTL position, while the MARK method was most efficient when the causative SNP was included as a marker in the analysis. The LLDMARK method, combining association mapping and LLD, assumes a QTL as the null hypothesis (using LLD method) and tests whether the ‘putative causative SNP’ explains significantly more variance than a QTL in the region. Thus, if the putative causative SNP does not only give an Identical‐By‐Descent (IBD) signal, but also an Alike‐In‐State (AIS) signal, LLDMARK gives a positive likelihood ratio. LLDMARK detected less than half as many causative SNPs as the other methods, and also had a relatively high false discovery rate when the QTL effect was large. LLDMARK may however be more robust against spurious associations, because the regional IBD is largely corrected for by fitting a QTL effect in the null hypothesis model. 相似文献
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Demeure O Sanchez MP Riquet J Iannuccelli N Demars J Fève K Kernaleguen L Gogué J Billon Y Caritez JC Milan D Bidanel JP 《Journal of animal science》2005,83(9):1979-1987
Pig chromosome 7 (SSC 7) has been shown to be rich in QTL affecting performance and quality traits. Most studies mapped the QTL close to the swine leukocyte antigens (SLA), which has a large effect on adaptability and natural selection. Previous comparative mapping studies suggested that the 15-cM region limited by markers LRA1 (mapped at 55 cM) and S0102 (mapped at 70 cM) contains hundreds of genes. To decrease the number of candidate genes, we improved the mapping resolution with a genetic chromosome dissection through a backcross recombinant progeny test program between Meishan (MS) and European (EU; i.e., Large White or Landrace) breeds. Three first-generation backcross--(EU x MS) x EU--and two second-generation backcross--([EU x MS] x EU) x EU--sires carrying a recombination in the QTL mapping interval were progeny-tested (i.e., measured for a total of 44 growth, fatness, carcass and meat quality traits). Progeny family size varied from 29 to 119 pigs. Animals were genotyped for markers covering the region of interest. Progeny-test results allowed the QTL interval to be decreased from 15 to 20 cM down to 10 cM, and even less than 6 cM if we assumed that the EU pigs used in this study share only one QTL allele. Except for a putative QTL affecting some carcass composition traits, the SLA is excluded as a candidate region, suggesting that it might be possible to apply a marker-assisted selection strategy for this QTL, while controlling SLA allele diversity. The strong QTL effects remaining in animals with only 12.5% (issued from first-generation backcross boars) and 6.25% (issued from second-generation back-cross boars) Meishan genetic background shows that epistatic interactions are likely to be limited. Finally, the QTL does not have strong effects on meat quality traits. 相似文献
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Estimation of genome-wide haplotype effects in half-sib designs 总被引：2，自引：1，他引：1
D. Kolbehdari L.R. Schaeffer & J.A.B. Robinson 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2007,124(6):356-361
Genome-wide estimated breeding values can be computed from the simultaneous estimates of the effects of small intervals of DNA throughout the genome on a trait or traits of interest. Small intervals or segments of DNA can be created by the use of thousands of single nucleotide polymorphisms (SNP) available in panels of 10, 25 and 50 thousand SNP. A simulation study was conducted to compare factors that could influence the accuracy of genome-wide selection. Factors studied were the heritability of the trait, dispersion of quantitative trait loci (QTL) across the genome and size of the QTL effects. A 100-cM genome was assumed with 100 equally spaced SNP markers and 10 QTL. A granddaughter design was constructed with 20 sires and 100 sons per sire. Population-wide linkage disequilibrium was assumed to be sufficient after 25 generations of random mating starting with 30 sires and 400 dams. Best linear unbiased prediction was used to simultaneously estimate the effects of 99 SNP intervals, based on determining the SNP haplotype of each son inherited from the sire. Indicator variables were used in the model to indicate haplotype transmission. A genome-wide estimated breeding value was calculated as the sum of the appropriate haplotype interval estimates for each son. Correlations between estimated and true breeding values ranged from 0.60 to 0.79. Situations with unequally sized QTL effects and randomly dispersed QTL gave higher correlations. QTL positions could be estimated to within 2 cM or less. 相似文献