高通量测序技术结合正向遗传学手段在基因定位研究中的应用

传统的利用正向遗传学方法的基因定位一般是通过构建遗传连锁图谱进行的,该过程步骤繁琐、耗时耗力,很多情形下定位精确度低、区间大。随着高通量测序技术的快速发展以及测序成本的不断降低,多种简单快捷的利用测序手段定位基因的方法被开发出来,包括对突变体基因组直接测序定位、突变体材料构建混池测序定位和遗传分离群体测序构建图谱定位等,还可以对转录组和部分基因组进行测序定位。这些方法可以在核苷酸水平鉴定突变位点,并已推广到复杂的遗传背景中。近期报道的一些测序定位甚至是在不依赖于参考基因组序列、遗传杂交和连锁信息的情况下完成的,这使得很多非模式物种也能开展正向遗传学研究。本文就这些新技术及其在基因定位中的应用进行了综述。     

ＥＳＴ在克隆新基因中的应用

随着基因定位（连锁图谱、物理图谱、转录图谱）和ＤＮＡ测序及生物信息技术的迅猛发展,ＥＳＴ已成为人类寻找新的未知基因以及克隆不同时空差异表达基因和疾病相关基因的重要标志物。随着ＥＳＴ数据库的进一步完善,网上克隆和定位候选克隆策略将成为克隆新基因的主要方法,并在虚拟的网上空间将模型生物基因组的研究成果成功地应用于人类基因组的研究中。     

蛋白质基因组学：运用蛋白质组技术注释基因组

随着高通量DNA测序技术的飞速发展,越来越多的物种完成了基因组测序．定位编码基因、确定编码基因结构是基因组注释的基本任务,然而以往的基因组注释方法主要依赖于DNA及RNA序列信息．为了更加精确地解读完成测序的基因组,我们需要整合多种类型的组学数据进行基因组注释．近年来,基于串联质谱技术的蛋白质组学已经发展成熟,实现了对蛋白质组的高覆盖,使得利用串联质谱数据进行基因组注释成为可能．串联质谱数据一方面可以对已注释的基因进行表达验证,另一方面还可以校正原注释基因,进而发现新基因,实现对基因组序列的重新注释．这正是当前进展较快的蛋白质基因组学的研究内容．利用该方法系统地注释已完成测序的基因组已成为解读基因组的一个重要补充．本文综述了蛋白质基因组学的主要研究内容和研究方法,并展望了该研究方向未来的发展．     

水稻基因图

水稻基因组计划要完成4张图:遗传图、物理图、序列图以及转录图,它们是进行基因定位与基因克隆的重要工具。水稻是模式植物,其全基因组测序的完成、丰富的遗传资源和多个基因组研究数据库,极大地推动和加速了水稻基因图的绘制。对基因图绘制的原理及在水稻中的应用进行了论述。     

用人工神经网络方法确定真核基因启动子

本文运用神经网络方法,并结合分子生物学的有关理论与实验统计事实,对真核基因启动子区域进行了识别．文中选择了人类、牛、猪、猫、山羊、兔、绵羊、大鼠、小鼠、小马、仓鼠、鸡、鸭、大豆等共13种真核生物360个基因组,作为研究对象．学习组选择了300个基因组,预测组选择了60基因组．结果表明,将神经网络模型与基因理论相结合,能够运用计算方法,从大量的可能启动子组合中排列出唯一的启动子区域．     

转Xa21基因水稻中T-DNA整合的遗传定位

利用转抗白叶枯病基因Xa21的水稻材料,通过TAIL－PCR方法扩增T－DNA整合的侧翼序列。从中筛选属于水稻基因组DNA的T－DNA整合的侧翼序列作为探针,将外源基因整合位点定位到窄叶青／京系17DH群体构建的水稻分子连锁图谱上。共获得属于水稻基因组DNA的T－DNA侧翼序列22个,其中的19个序列在定位群体的两个亲本之间显示RFLP多态性,分别定位在水稻基因组的第3,4,5,7,9,10,11和12染色体上。带有转基因Xa21的T－DNA整合的定位为研究外源基因在不同染色体位点的位置效应和稳定遗传打下基础。     

医学分子遗传学 第八讲重组DNA 执术与基因定位

人体基因组是一个十分复杂的结构，每单倍体基因组大约有3*10⁹bp组成，分成22条常染色体和1条性染色体。据估计，在人体基因组上存在着大约50,000--100,000个结构基因，平均每分摩(cM)染色体五分布着20个结构基因。人体基因组大约有33cM，由此推算出人体基因组上含有约66,000个结构基因。现在已经明确地鉴定七了1,600多个人体基因，其中约有1,000多个基因定位在特定的染色体上。基因定位是研究遗传性疾病和肿瘤发病机制及进行基因诊断的基础。因此，基因定位研究的迅速发展，对于揭示遗传病和肿瘤发病机制的本质，对于预防和治疗遗传性疾病和肿瘤都将起到重要的促进和推动作用。     

互作基因定位方法的研究和计算机软件的开发

质量性状中存在6种可能的基因互作类型, 即互补、重叠、累加、显性上位、隐性上位和抑制。在遗传研究中, 有时会遇到互作基因定位的问题, 但至今未见有关互作基因定位方法和计算机软件的系统的研究报道。文章给出了基于极大似然估计的互作基因定位方法及相应的计算机软件(IGMapping 1.0)。计算机模拟表明, 此方法可以无偏地估计一个共显性标记与一个互作基因之间的重组率或连锁距离。     

用富集文库克隆人胰岛素基因组基因

通过构建可富集人胰岛素基因的λ噬菌体文库,克隆了人胰岛素基因组基因．首先从中国人血液白细胞中提取到人基因组ＤＮＡ,用ＥｃｏＲⅠ和ＢｇｌⅡ对基因组ＤＮＡ进行全酶切,经０．４％琼脂糖凝胶电泳,特异回收９．５ｋｂ左右的ＤＮＡ片段．将该片段与λＥＭＢＬ３／ＢａｍＨⅠ臂连接,构建成一个特殊的人基因组λ噬菌体文库（富集文库）,效价为２×１０４．同时采用ＰＣＲ方法及用引物Ⅰ：５′ＧＧＡＣＡＧＧＣＴＡＣＡＴＣＡＧＧＡＡＧＡＧＧ３′,引物Ⅱ：５′ＣＴＧＣＧＴＣＴＡＡＴＴＧＣＡＧＴＡＧＴＴＣ３′,从人基因组ＤＮＡ中扩增出一段含胰岛素基因的１．３６ｋｂＤＮＡ片段,做为放射性标记探针,对文库进行了噬菌斑原位杂交筛选,从１×１０４个噬菌斑中筛选到一个含人胰岛素基因组基因的阳性克隆,并进一步完成了亚克隆和该基因１７３２ｂｐＤＮＡ序列的测定．结果该基因的１７３２ｂｐＤＮＡ序列包括部分５′端和３′端与国外发表的人胰岛素α型等位基因的序列相同     

原核基因翻译起始位点预测的新方法

翻译起始位点（TIS,即基因5’端）的精确定位是原核生物基因预测的一个关键问题,而基因组GC含量和翻译起始机制的多样性是影响当前TIS预测水平的重要因素．结合基因组结构的复杂信息（包括GC含量、TIS邻近序列及上游调控信号、序列编码潜能、操纵子结构等）,发展刻画翻译起始机制的数学统计模型,据此设计TIS预测的新算法MED．StartPlus．并将MED．StartPlus与同类方法RBSfinder、GS．Finder、MED-Start、TiCo和Hon-yaku等进行系统地比较和评价．测试针对两种数据集进行：当前14个已知的TIS被确认的基因数据集,以及300个物种中功能已知的基因数据集．测试结果表明,MED-StartPlus的预测精度在总体上超过同类方法．尤其是对高GC含量基因组以及具有复杂翻译起始机制的基因组,MED-StartPlus具有明显的优势．     

Complete multipoint sib-pair analysis of qualitative and quantitative traits.

Sib-pair analysis is an increasingly important tool for genetic dissection of complex traits. Current methods for sib-pair analysis are primarily based on studying individual genetic markers one at a time and thus fail to use the full inheritance information provided by multipoint linkage analysis. In this paper, we describe how to extract the complete multipoint inheritance information for each sib pair. We then describe methods that use this information to map loci affecting traits, thereby providing a unified approach to both qualitative and quantitative traits. Specifically, complete multipoint approaches are presented for (1) exclusion mapping of qualitative traits; (2) maximum-likelihood mapping of qualitative traits; (3) information-content mapping, showing the extent to which all inheritance information has been extracted at each location in the genome; and (4) quantitative-trait mapping, by two parametric methods and one nonparametric method. In addition, we explore the effects of marker density, marker polymorphism, and availability of parents on the information content of a study. We have implemented the analysis methods in a new computer package, MAPMAKER/SIBS. With this computer package, complete multipoint analysis with dozens of markers in hundreds of sib pairs can be carried out in minutes.     

Convergent evolution with combinatorial peptides

Once the sequence of a genome is in hand, understanding the function of its encoded proteins becomes a task of paramount importance. Much like the biochemists who first outlined different biochemical pathways, many genomic scientists are engaged in determining which proteins interact with which proteins, thereby establishing a protein interaction network. While these interactions have evolved in regard to their specificity, affinity and cellular function over billions of years, it is possible in the laboratory to isolate peptides from combinatorial libraries that bind to the same proteins with similar specificity, affinity and primary structures, which resemble those of the natural interacting proteins. We have termed this phenomenon 'convergent evolution'. In this review, we highlight various examples of convergent evolution that have been uncovered in experiments dissecting protein-protein interactions with combinatorial peptides. Thus, a fruitful approach for mapping protein-protein interactions is to isolate peptide ligands to a target protein and identify candidate interacting proteins in a sequenced genome by computer analysis.     

A new strategy to reduce allelic bias in RNA-Seq readmapping

Accurate estimation of expression levels from RNA-Seq data entails precise mapping of the sequence reads to a reference genome. Because the standard reference genome contains only one allele at any given locus, reads overlapping polymorphic loci that carry a non-reference allele are at least one mismatch away from the reference and, hence, are less likely to be mapped. This bias in read mapping leads to inaccurate estimates of allele-specific expression (ASE). To address this read-mapping bias, we propose the construction of an enhanced reference genome that includes the alternative alleles at known polymorphic loci. We show that mapping to this enhanced reference reduced the read-mapping biases, leading to more reliable estimates of ASE. Experiments on simulated data show that the proposed strategy reduced the number of loci with mapping bias by ≥63% when compared with a previous approach that relies on masking the polymorphic loci and by ≥18% when compared with the standard approach that uses an unaltered reference. When we applied our strategy to actual RNA-Seq data, we found that it mapped up to 15% more reads than the previous approaches and identified many seemingly incorrect inferences made by them.     

SSRscanner: a program for reporting distribution and exact location of simple sequence repeats

Simple sequence repeats (SSRs) have become important molecular markers for a broad range of applications, such as genome mapping and characterization, phenotype mapping, marker assisted selection of crop plants and a range of molecular ecology and diversity studies. These repeated DNA sequences are found in both prokaryotes and eukaryotes. They are distributed almost at random throughout the genome, ranging from mononucleotide to trinucleotide repeats. They are also found at longer lengths (> 6 repeating units) of tracts. Most of the computer programs that find SSRs do not report its exact position. A computer program SSRscanner was written to find out distribution, frequency and exact location of each SSR in the genome. SSRscanner is user friendly. It can search repeats of any length and produce outputs with their exact position on chromosome and their frequency of occurrence in the sequence.

Availability     

Analytical correction for multiple testing in admixture mapping

Admixture mapping, using unrelated individuals from the admixture populations that result from recent mating between members of each parental population, is an efficient approach to localize disease-causing variants that differ in frequency between two or more historically separated populations. Recently, several methods have been proposed to test linkage between a susceptibility gene and a disease locus by using admixture-generated linkage disequilibrium (LD) for each of the genotyped markers. In a genome scan, admixture mapping usually tests 2,000 to 3,000 markers across the genome. Currently, either a very conservative Sidak (or Bonferroni) correction or a very time consuming simulation-based method is used to correct for the multiple tests and evaluate the overall p value. In this report, we propose a computationally efficient analytical approach for correction of the multiple tests and for calculating the overall p value for an admixture genome scan. Except for the Sidak (or Bonferroni) correction, our proposed method is the first analytical approach for correction of the multiple tests and for calculating the overall p value for a genome scan. Our simulation studies show that the proposed method gives correct overall type I error rates for genome scans in all cases, and is much more computationally efficient than simulation-based methods.     

Variation in recombination rate may bias human genetic disease mapping studies

The availability of the human genome sequence and variability information (as from the International HapMap project) will enhance our ability to map genetic disorders and choose targets for therapeutic intervention. However, several factors, such as regional variation in recombination rate, can bias conclusions from genetic mapping studies. Here, we examine the impact of regional variation in recombination rate across the human genome. Through computer simulations and literature surveys, we conclude that genetic disorders have been mapped to regions of low recombination more often than expected if such diseases were randomly distributed across the genome. This concentration in low recombination regions may be an artifact, and disorders appearing to be caused by a few genes of large effect may be polygenic. Future genetic mapping studies should be conscious of this potential complication by noting the regional recombination rate of regions implicated in diseases.     

Fine-scale mapping in Neurospora crassa by using genome-wide knockout strains

Fine-scale genetic mapping is often hindered by the lack of adequate markers surrounding the locus of interest. In the filamentous ascomycete Neurospora crassa, the genome has been sequenced and an effort has been made to generate genome-wide deletion strains for the entire gene set. Accordingly, the hygromycin-resistant marker in each deletion strain can be used as a mapping locus in a classical three-point cross, along with the mapping target and a standard marker. We have demonstrated the feasibility of this fine-scale mapping approach in N. crassa by refining the location of r(Sk-2).