X染色体印记效应检验及合并X染色体失活与印记效应的关联分析研究
发布时间：2018-08-25 12:22
【摘要】：背景:关联分析(association analysis)是用来检验等位基因频率或基因型频率在两组个体(患病人群和正常人群)之间是否存在差异的方法。其主要目的是为了定位疾病位点,利用疾病位点和标记位点的关系来找到遗传变异。如果标记位点和疾病位点之间的距离很接近,它们可能存在连锁不平衡(linkage disequilibrium),那么这两个位点很有可能是共同遗传给后代的。如果在患病的人群中这个标记位点的频率比正常人群的高,利用关联分析方法就可能将该疾病位点进行定位。遗传印记效应(genomic imprinting)是我们熟知的一种病因学因素。遗传印记基因的表达取决于等位基因是来自父亲还是来自母亲,而这种现象可能会导致疾病和基因之间的关联。遗传印记现象会影响后代在子宫内的发育以及出生后个体的成长发育。与常染色体上变异的遗传印记作用有关的疾病有:Beckwith-Wiedemann 综合征、Prader-Will 综合征、Angelman 综合征、糖尿病和精神分裂症等。另外,X染色体上的印记基因在复杂疾病和性状的形成上也许起到了关键的作用,如Turner综合征和孤独症等。目前已经有很多方法可以用来检验基于核心家庭和一般家系常染色体上的遗传印记效应。有关X染色体上印记效应的检验,仅仅有最近新提出的基于核心家庭数据的X染色体质量性状位点上的亲代不对称检验方法(parental-asymmetry test on X chromosome,XPAT)。然而该方法并不适用于一般的家系数据。X 染色体失活(X chromosome inactivation,XCI)是一种剂量补偿(dose compensation)的机制,通常发生在胚胎发育早期,女性的两条X染色体中的一条发生了失活现象,从而导致女性个体的每一个细胞中,只有一条来自父亲或者母亲的染色体表达。通常,这种X染色体失活的现象是随机的,即女性的两条X染色体失活的比例是50%:50%。但是,如果失活现象不是随机的,那就称之为偏倚失活(skewed X chromosome inactivation)。偏倚失活通常意味着有75%或以上的细胞失活同一条X染色体,而另外25%的细胞失活另一条X染色体。另外,跟常染色体一样,X染色体还存在着一种特殊现象就是逃逸失活(escape from X chromosome inactivation)的情况,即两条X染色体均表达,没有失活。在一些女性个体中的某一条X染色体上,大概有四分之三的基因是沉默了的,其余四分之一的基因属于逃逸失活区域。然而,现有的X染色体上的关联分析方法中,仅考虑了 X染色体失活,并没有合并遗传印记的效应。因此,本文的研究目的主要有以下两点:(1)基于家系数据,提出X染色体质量性状位点上遗传印记效应检验方法;(2)基于两代人的病例对照数据,提出同时合并X染色体失活和印记效应的关联分析方法。方法:(1)考虑X染色体上的位点,参考常染色体上的PPAT方法,利用家系中所有有信息的核心家庭,当感兴趣的SNP位点与疾病之间存在关联的情况下,提出基于家系数据的X染色体亲代不对称检验方法(pedigree parental-asymmetry test on X chromosome,XPPAT)。当某些家系中存在缺失基因型个体时,我们根据观察到的个体基因型,采用Monte Carlo重抽样方法对缺失个体的基因型进行反推,进一步提出基于家系数据的X染色体Monte Carlo亲代不对称检验方法(Monte Carlo pedigree parental-asymmetry test on X chromosome,XMCPPAT)。通过模拟得到所提出方法的第一类错误率和检验效能。最后,通过一个来自北美的类风湿关节炎基因数据对新提出方法进行实例验证。(2)参考Wang等人提出的最大化似然比的检验方法,针对不同的X染色体失活模式(随机失活、偏倚失活和逃逸失活),将一个个体来自父亲和母亲的等位基因分别进行赋值。对女性的等位基因进行赋值时,用r∈[0,2]来衡量X染色体失活的偏倚程度,然后通过男性的等位基因赋值来体现X染色体是否失活。而这种赋值方式的效应量可以体现印记效应是否存在。这样可以将X染色体失活和遗传印记效应的信息同时合并到Logistic回归模型中。对不同的r值,得到不同的LR值,记为LRr。取LRr的最大值作为检验统计量,注意到其在无关联的原假设下的分布未知。所以,我们还采用了一种permutation的方法得到新提出方法的经验P值进行统计推断。相应的方法记为XCII方法(association test incorporating X chromosome inactivation and imprinting effects)。通过模拟得到所提出方法的第一类错误率和检验效能。结果:(1)在不同的模拟背景下,包括两种不同的样本量、两组不同的等位基因频率、三种不同的近交系数和五种不同的遗传印记效应模型,模拟结果表明所提出的方法可以很好地控制第一类错误率。并且,新方法的检验效能比现有的XPAT方法要高出很多。通过Monte Carlo重抽样方法对缺失基因型进行反推,XMCPPAT方法在存在缺失基因型个体时能控制第一类错误率。再者,由于女性中近交系数的改变对XPPAT和XMCPPAT方法的结果几乎不产生影响,因而新提出的XPPAT和XMCPPAT方法不受女性中Hardy-Weinberg平衡律(Hardy-Weinberg equilibrium,HWE)是否成立的影响。值得注意的是,对适用于缺失数据的XMCPPAT方法,我们采用了三种方式对等位基因频率进行处理,包括:真实的等位基因频率、由女性奠基者估算出的等位基因频率和由男性奠基者估算出的等位基因频率,将统计量分别记为XMCPPATt、XMCPPATf和XMCPPATm。另外,基于完整数据,用XPPATfull进行检验,作为所有方法的金标准。从结果上看,应用女性奠基者估算出的等位基因频率的XMCPPATf方法与基于完整数据的XPPATfull方法以及基于真实的等位基因频率的XMCPPATt方法检验效能很接近。这意味着,XMCPPATt和XMCPPATf方法可以捕获大部分缺失基因型个体的信息。然而,XMCPPATm不能很好地控制第一类错误率。(2)模拟结果表明,XCII方法可以将第一类错误率稳定在设定的显著性水平附近,说明了 XCII方法用以检验合并X染色体失活与印记效应信息的位点与疾病之间关联的有效性。在检验效能方面,当X染色体失活和遗传印记效应同时存在时,XCII方法的检验效能整体上比Wang的方法高。当仅有X染色体失活而印记效应不存在时,XCII方法的检验效能仍比Wang的方法高。因此,考虑X染色体上的关联分析研究时,我们更推荐使用第三章新提出的XCII方法。结论:(1)新提出的XPPAT和XMCPPAT检验统计量可以有效地检验基于家系数据的X染色体质量性状位点上的印记效应,XMCPPAT方法比现有的方法检验效能更高,更适用于对包含缺失基因型个体的数据进行印记效应的检验。(2)考虑X染色体上的关联分析研究时,很多疾病同时跟X染色体失活和遗传印记效应相关联,相比只考虑X染色体失活的Wang的方法,XCII方法的表现更好。因此,我们推荐使用同时考虑X染色体失活和印记效应的XCII方法。
[Abstract]:BACKGROUND: Association analysis is a method used to test whether allele frequencies or genotype frequencies differ between two groups of individuals (the sick and the normal). The main purpose of association analysis is to locate disease sites and use the relationship between disease sites and marker sites to find genetic variations. If the frequency of this marker is higher in the affected population than in the normal population, it is possible to locate the disease site by association analysis. Genetic imprinting is a well-known etiological factor. The expression of genetic imprinting genes depends on whether the allele is from the father or the mother, and this phenomenon may lead to disease and gene association. Genetic imprinting affects the development of offspring in the uterus and the development of individuals after birth. Diseases associated with genetic imprinting of autosomal variations include Beckwith-Wiedemann syndrome, Prader-Will syndrome, Angelman syndrome, diabetes and schizophrenia. In addition, imprinting genes on the X chromosome may play a key role in the formation of complex diseases and characteristics, such as Turner syndrome and schizophrenia. Autism and so on. At present, there are many methods which can be used to test the genetic imprinting effect on autosomal chromosomes of nuclear families and general families. X chromosome inactivation (XCI) is a dose compensation mechanism, usually occurring in the early embryonic development, in which one of the two X chromosomes of a woman is inactivated, leading to a female individual. In each cell, only one chromosome is expressed from the father or mother. Usually, this X-chromosome inactivation is random, i.e. the ratio of two X-chromosomes inactivation in women is 50%:50%. However, if the inactivation is not random, it is called skewed X-chromosome inactivation. Usually it means that 75% or more of the cells are inactivated on the same X chromosome, while 25% of the cells are inactivated on the other X chromosome. About three-quarters of the genes on an X chromosome are silent, and the remaining one-quarter belong to the escape-inactivation region. The following two points are pointed out: (1) Based on the family coefficient data, a method for testing the genetic imprinting effect on the quality trait loci of X chromosome is proposed; (2) Based on the case-control data of two generations, an association analysis method combining both X chromosome inactivation and imprinting effect is proposed. A pedigree parental-asymmetric test on X chromosome (XPPAT) based on family coefficient data is proposed for all informative nuclear families in a family. When there are deleted genotypes in some families, we use the observed ones. The genotypes of deleted individuals were retrieved by Monte Carlo resampling method, and the Monte Carlo parental asymmetry test on X chromosome (XMCPPAT) based on family coefficient data was proposed. The first class error rate and XMCPPAT of the proposed method were obtained by simulation. Finally, the proposed method was validated by a North American rheumatoid arthritis gene data set. (2) Referring to the maximum likelihood ratio test proposed by Wang et al., an individual was selected from his father and mother for different X chromosome inactivation patterns (random inactivation, bias inactivation and escape inactivation). When assigning female alleles, the bias of X-chromosome inactivation is measured by R < [0,2], and then the X-chromosome inactivation is reflected by the male allele assignment. The effect of this assignment can reflect the existence of imprinting effect. This can inactivate and lose X-chromosome. The information of biography effect is merged into the logistic regression model at the same time. Different values of R are obtained, which are recorded as LR R. The maximum of LR R is taken as the test statistic and the distribution of LR R is unknown under the original assumption of irrelevance. Therefore, we also use a permutation method to obtain the empirical P value of the new method. Statistical inference. The corresponding method is called the association test incorporating X chromosome inactivation and imprinting effects. Three different inbreeding coefficients and five different genetic imprinting effect models were used to simulate the results. The simulation results show that the proposed method can control the first kind of error rate very well. Moreover, the test efficiency of the new method is much higher than that of the existing XPAT method. Moreover, since the change of inbreeding coefficient in women has little effect on the results of XPPAT and XMCPPAT methods, the new XPPAT and XMCPPAT methods are not affected by the Hardy-Weinberg equilibrium (HWE) in women. Yes, for the XMCPPAT method applicable to missing data, we used three methods to process allele frequencies, including true allele frequencies, allele frequencies estimated by female founders, and allele frequencies estimated by male founders. The statistics were recorded as XMCPPATt, XMCPPATf, and XMCPPATm, respectively. The results showed that the XMCPPATf method based on the allele frequencies estimated by the female founders was very close to the XPPATful method based on the complete data and the XMCPPATt method based on the true allele frequencies. Tt and XMCPPATf methods can capture the information of most deleted genotypes. However, XMCPPATm can not control the first class error rate very well. (2) Simulation results show that XCII method can stabilize the first class error rate near the set significance level, indicating that XCII method is used to test the combined X chromosome inactivation and imprinting effect letter. When X chromosome inactivation and genetic imprinting effect coexist, the efficiency of XCII method is higher than that of Wang's method on the whole. When only X chromosome is inactivated and imprinting effect does not exist, the efficiency of XCII method is still higher than that of Wang's method. Conclusion: (1) The newly proposed XPPAT and XMCPPAT test statistic can effectively test the imprinting effect on X chromosome quality trait loci based on family coefficient data. The XMCPPAT method is more effective than the existing methods and is more suitable for detecting inclusion deficiencies. (2) Considering X-chromosome Association analysis, many diseases are associated with both X-chromosome inactivation and genetic imprinting. The XCII method performs better than Wang's method, which only considers X-chromosome inactivation. Therefore, we recommend that both X-chromosome inactivation and X-chromosome inactivation be considered. And the imprinting effect of XCII method.
【学位授予单位】：南方医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R394
，
本文编号：2202875
[Abstract]:BACKGROUND: Association analysis is a method used to test whether allele frequencies or genotype frequencies differ between two groups of individuals (the sick and the normal). The main purpose of association analysis is to locate disease sites and use the relationship between disease sites and marker sites to find genetic variations. If the frequency of this marker is higher in the affected population than in the normal population, it is possible to locate the disease site by association analysis. Genetic imprinting is a well-known etiological factor. The expression of genetic imprinting genes depends on whether the allele is from the father or the mother, and this phenomenon may lead to disease and gene association. Genetic imprinting affects the development of offspring in the uterus and the development of individuals after birth. Diseases associated with genetic imprinting of autosomal variations include Beckwith-Wiedemann syndrome, Prader-Will syndrome, Angelman syndrome, diabetes and schizophrenia. In addition, imprinting genes on the X chromosome may play a key role in the formation of complex diseases and characteristics, such as Turner syndrome and schizophrenia. Autism and so on. At present, there are many methods which can be used to test the genetic imprinting effect on autosomal chromosomes of nuclear families and general families. X chromosome inactivation (XCI) is a dose compensation mechanism, usually occurring in the early embryonic development, in which one of the two X chromosomes of a woman is inactivated, leading to a female individual. In each cell, only one chromosome is expressed from the father or mother. Usually, this X-chromosome inactivation is random, i.e. the ratio of two X-chromosomes inactivation in women is 50%:50%. However, if the inactivation is not random, it is called skewed X-chromosome inactivation. Usually it means that 75% or more of the cells are inactivated on the same X chromosome, while 25% of the cells are inactivated on the other X chromosome. About three-quarters of the genes on an X chromosome are silent, and the remaining one-quarter belong to the escape-inactivation region. The following two points are pointed out: (1) Based on the family coefficient data, a method for testing the genetic imprinting effect on the quality trait loci of X chromosome is proposed; (2) Based on the case-control data of two generations, an association analysis method combining both X chromosome inactivation and imprinting effect is proposed. A pedigree parental-asymmetric test on X chromosome (XPPAT) based on family coefficient data is proposed for all informative nuclear families in a family. When there are deleted genotypes in some families, we use the observed ones. The genotypes of deleted individuals were retrieved by Monte Carlo resampling method, and the Monte Carlo parental asymmetry test on X chromosome (XMCPPAT) based on family coefficient data was proposed. The first class error rate and XMCPPAT of the proposed method were obtained by simulation. Finally, the proposed method was validated by a North American rheumatoid arthritis gene data set. (2) Referring to the maximum likelihood ratio test proposed by Wang et al., an individual was selected from his father and mother for different X chromosome inactivation patterns (random inactivation, bias inactivation and escape inactivation). When assigning female alleles, the bias of X-chromosome inactivation is measured by R < [0,2], and then the X-chromosome inactivation is reflected by the male allele assignment. The effect of this assignment can reflect the existence of imprinting effect. This can inactivate and lose X-chromosome. The information of biography effect is merged into the logistic regression model at the same time. Different values of R are obtained, which are recorded as LR R. The maximum of LR R is taken as the test statistic and the distribution of LR R is unknown under the original assumption of irrelevance. Therefore, we also use a permutation method to obtain the empirical P value of the new method. Statistical inference. The corresponding method is called the association test incorporating X chromosome inactivation and imprinting effects. Three different inbreeding coefficients and five different genetic imprinting effect models were used to simulate the results. The simulation results show that the proposed method can control the first kind of error rate very well. Moreover, the test efficiency of the new method is much higher than that of the existing XPAT method. Moreover, since the change of inbreeding coefficient in women has little effect on the results of XPPAT and XMCPPAT methods, the new XPPAT and XMCPPAT methods are not affected by the Hardy-Weinberg equilibrium (HWE) in women. Yes, for the XMCPPAT method applicable to missing data, we used three methods to process allele frequencies, including true allele frequencies, allele frequencies estimated by female founders, and allele frequencies estimated by male founders. The statistics were recorded as XMCPPATt, XMCPPATf, and XMCPPATm, respectively. The results showed that the XMCPPATf method based on the allele frequencies estimated by the female founders was very close to the XPPATful method based on the complete data and the XMCPPATt method based on the true allele frequencies. Tt and XMCPPATf methods can capture the information of most deleted genotypes. However, XMCPPATm can not control the first class error rate very well. (2) Simulation results show that XCII method can stabilize the first class error rate near the set significance level, indicating that XCII method is used to test the combined X chromosome inactivation and imprinting effect letter. When X chromosome inactivation and genetic imprinting effect coexist, the efficiency of XCII method is higher than that of Wang's method on the whole. When only X chromosome is inactivated and imprinting effect does not exist, the efficiency of XCII method is still higher than that of Wang's method. Conclusion: (1) The newly proposed XPPAT and XMCPPAT test statistic can effectively test the imprinting effect on X chromosome quality trait loci based on family coefficient data. The XMCPPAT method is more effective than the existing methods and is more suitable for detecting inclusion deficiencies. (2) Considering X-chromosome Association analysis, many diseases are associated with both X-chromosome inactivation and genetic imprinting. The XCII method performs better than Wang's method, which only considers X-chromosome inactivation. Therefore, we recommend that both X-chromosome inactivation and X-chromosome inactivation be considered. And the imprinting effect of XCII method.
【学位授予单位】：南方医科大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R394
，
本文编号：2202875
本文链接：https://www.wllwen.com/yixuelunwen/jichuyixue/2202875.html
