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苜蓿遗传图谱构建及其应用 总被引：10，自引：6，他引：4
苜蓿是世界上最重要的豆科牧草之一,苜蓿遗传图谱构建是解析重要农艺性状(QTL)遗传特性和基因连锁分析的前提条件。由于复杂的四体遗传特性,目前已构建成功的苜蓿遗传图谱大多数是二倍体苜蓿,四倍体栽培苜蓿遗传图谱较少。本研究就苜蓿遗传图谱构建研究已取得的成就、图谱绘制过程中的限制因素、解决策略和已有图谱的特征等问题进行了回顾和讨论;对苜蓿遗传图谱研究,特别是构建四倍体苜蓿遗传图谱,在揭示苜蓿遗传特性和定位重要农艺性状相关基因位点(QTL)方面的应用现状和重要意义进行了论述,就苜蓿遗传图谱在苜蓿分子标记辅助育种中的应用前景进行了展望,并就我国苜蓿育种现状和开展苜蓿遗传图谱构建研究提出了一些建议。 相似文献
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分别以早熟低产和晚熟高产苜蓿单株为父母本,通过人工杂交构建了四倍体紫花苜蓿(Medicago Sativa)F1遗传作图群体,采用单因子变量分析法,以降落式PCR和常规PCR结合的反应程序,建立了适宜于紫花苜蓿的分子标记扩增体系;应用130对SSR引物进行筛选,获得60对引物在父母本间存在多态性而被用于绘制遗传连锁图。采用PAGE电泳分析,对作图群体进行基因型分析。通过TetraploidMap软件对60个SSR标记进行连锁作图分析,有44个标记可以定位在8个连锁群上,占总标记数的33.8%,覆盖遗传距离979 cM,两标记间平均图距为22.25 cM,初步构建了四倍体紫花苜蓿遗传图谱的框架图,还需要进一步添加标记数量增大其饱和度,为重要性状的QTL定位奠定基础。 相似文献
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为了给后期马铃薯块茎高淀粉、高干物质及产量等重要数量性状基因座(QTL)定位和分子标记辅助育种奠定基础,以四倍体马铃薯YSP-4×MIN-021杂种F1的182个分离单株为作图群体,利用相关序列扩增多态性(SRAP)分子标记进行了遗传图谱构建研究。试验从357对SRAP引物中筛选出适宜引物36对。用这些引物对马铃薯杂种F1的182个分离单株及其亲本的基因组DNA进行PCR扩增得到598个SRAP标记。卡方检验显示偏分离标记数为127个,其中母本连锁群59个,父本连锁群68个,偏分离比率均小于30%,符合遗传作图的要求。用软件JoinMap4.0建立了2张四倍体马铃薯双亲的SRAP遗传图谱。母本YSP-4的连锁群总长度为1572.2cM,标记数目为274个,平均间距为5.74cM,12个连锁群的长度范围为14.03~214.44cM;父本MIN-021的连锁群总长度为1932.23cM,标记数目为324个,平均间距为5.96cM,各连锁群的长度范围为93.65~242.06cM。 相似文献
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为构建四倍体杂交冰草分子遗传连锁图谱,对深入开展冰草产量、抗性等重要性状的QTL定位及分子标记辅助育种提供依据,以四倍体杂种F2分离群体的347个单株及亲本蒙古冰草和航道冰草为材料,采用SSR分子标记技术和Joinmap 4.0软件进行了遗传作图研究。试验从256对SSR引物中筛选出条带清晰稳定、多态性丰富的适宜引物30对,PCR扩增得到224个SSR标记位点,平均每对引物扩增出7.47个位点,其中多态性标记位点185个,占82.6%。偏分离分析显示,在185个SSR多态性标记位点中有24个标记产生偏分离,占13.0%,符合植物遗传作图时通常偏分离标记比率<30%的要求,可用于遗传作图。构建了1张四倍体杂交冰草的分子遗传连锁框架图谱,该图谱包含14个连锁群、185个标记,其长度范围在123.0~202.6 cM之间,连锁群LG4最长、LG12最短,各连锁群的平均长度167.32 cM,覆盖基因组总长度2342.5 cM,标记间的平均距离12.66 cM。 相似文献
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产量相关性状是复杂的数量性状,对鸭茅的单株产量及构成因素进行QTL分析,可提高育种中对产量性状优良基因选择的效率,同时为鸭茅遗传改良、基因克隆及分子标记辅助育种提供理论依据。以四倍体鸭茅“楷模”和“01436”为亲本杂交而成的作图群体为试验材料,于2014年对洪雅、宝兴两个不同生境下鸭茅株高、旗叶长、倒二叶长、旗叶宽、倒二叶宽、茎粗、花序长、分蘖数、单株干重等9个产量相关性状进行了表型鉴定及相关性分析。此外,在已构建的高密度鸭茅分子遗传图谱的基础上,采用MapQTL 5.0进一步对这些性状QTL定位分析。结果表明,绝大多数性状在亲本间呈显著差异且都整体表现出连续变异,符合数量性状遗传的特征;相关性分析表明,大多数产量相关性状均与干重极显著正相关,与单株干重相关性最好的依次为分蘖、株高;QTL分析发现,控制该9个农艺性状的QTL共60个,洪雅38个,宝兴22个,这些QTL分别定位于分子连锁图谱的1、2、3、4、5共5个连锁群上,单个QTL的贡献率为5.7%~24.7%,单个性状QTL个数为2~15个。其中,控制株高、花序长的QTL各12个,控制倒二叶长、茎粗的QTL各4个,控制旗叶宽、倒二叶宽的QTL各2个,控制单株干重的QTL有6个,影响分蘖的QTL为3个,与旗叶长相关的QTL最多15个。 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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为初步鉴定与紫花苜蓿(Medicago sativa)粗灰分、钾、钙、镁、磷含量调控相关的数量性状基因座(Quantitative trait loci，QTL)和分子标记，本研究用低产早熟苜蓿和高产晚熟苜蓿杂交，构建了由392个个体组成的F1群体，对这些性状进行3年表型数据测定，且基于前期已构建的高密度遗传连锁图谱开展QTL定位。结果表明：共检测到63个与粗灰分和4种矿质元素含量相关的QTL，分布于22个染色体上，单个QTL的贡献率为2.50%~29.85%；其中重复定位的QTL共8个(qCa-3C-1和qCa-3C-2，qCa-6B-1和qCa-6B-2，qCa-6D-1和qCa-6D-2，qAsh-8B-1和qAsh-8B-2)，共定位的QTL有6个(qP-2C和qK-2C，qP-3A和qMg-3A，qP-6D-3和qMg-6D-2)；经进一步验证，与这些QTL紧密连锁的标记可用于分子标记辅助选择育种。本研究为选育矿质营养更丰富的苜蓿新品种奠定了基础。 相似文献
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从数量性状基因座作图到标记辅助选择 总被引：1，自引：0，他引：1
实现从数量性状基因座作图到标记辅助选择的转变包括 :( 1)寻找与QTL紧密连锁的标记 (被标记的QTL称MQTL) ;( 2 )精确估计MQTL的效应 ;( 3)将MQTL纳入现行的育种方案 ;( 4)改变现行的育种方案 ,拓展MAS的应用空间。 相似文献
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Genomic selection 总被引：2，自引：0，他引：2
Genomic selection is a form of marker-assisted selection in which genetic markers covering the whole genome are used so that all quantitative trait loci (QTL) are in linkage disequilibrium with at least one marker. This approach has become feasible thanks to the large number of single nucleotide polymorphisms (SNP) discovered by genome sequencing and new methods to efficiently genotype large number of SNP. Simulation results and limited experimental results suggest that breeding values can be predicted with high accuracy using genetic markers alone but more validation is required especially in samples of the population different from that in which the effect of the markers was estimated. The ideal method to estimate the breeding value from genomic data is to calculate the conditional mean of the breeding value given the genotype of the animal at each QTL. This conditional mean can only be calculated by using a prior distribution of QTL effects so this should be part of the research carried out to implement genomic selection. In practice, this method of estimating breeding values is approximated by using the marker genotypes instead of the QTL genotypes but the ideal method is likely to be approached more closely as more sequence and SNP data is obtained. Implementation of genomic selection is likely to have major implications for genetic evaluation systems and for genetic improvement programmes generally and these are discussed. 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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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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Ching Y. LIN 《Animal Science Journal》2008,79(1):22-28
This study quantified the efficiency of quantitative traits loci (QTL)‐assisted selection in the presence of correlations (ρqr) between identified (q) and residual (r) genotypes. Two levels of heritability (h2 = 0.1 or 0.3), two levels of correlation (ρqr = ?0.3 or 0.3) and five proportions of genetic variance explained by QTL detected (= 0.1, 0.2, 0.4, 0.6 or 0.8) were combined to give 20 scenarios in all. QTL‐assisted selection placed a larger index weight on the QTL genotype than on the phenotype in 17 of 20 scenarios, yielding a greater response in the QTL genotype than in residual genotype. Although QTL‐assisted selection was superior to phenotypic selection in all 20 scenarios, QTL‐assisted selection showed a greater advantage over phenotypic selection when ρqr was positive than when ρqr was negative. Doubling the proportion of detected QTL variance to genetic variance does not result in a twofold increase in the genetic response to QTL‐assisted selection, suggesting that economic returns diminish for each additional cost of detecting extra QTL. The correlation between q and r would make the interpretation (or prediction) of QTL effects difficult and QTL‐assisted selection strategy must consider the joint effect of q and r. When q and r are not independent, a failure to account for ρqr in QTL‐assisted selection would underestimate the genetic responses when ρqr is positive, but overestimate the genetic responses when ρqr is negative. Estimation bias is more serious at high heritability than at low heritability. Accounting for ρqr would improve the efficiency of QTL‐assisted selection and the accuracy of QTL detection. The generalized procedure developed in this study allows for quantifying the efficiency of QTL‐assisted selection and assessing estimation bias for ignoring the correlation between q and r for all possible combinations of h2, ρqr, and . 相似文献
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Francisco Joel Jahuey‐Martínez Gaspar Manuel Parra‐Bracamonte Ana María Sifuentes‐Rincn Victor Ricardo Moreno‐Medina 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2019,136(5):378-389
Charolais cattle are one of the most important breeds for meat production worldwide; in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8–59.3 Mb on BTA 4; 67.5–69.3 on BTA 5; 39.5–41.0 Mb on BTA 6; and 26.4–29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits. 相似文献