植物的单核苷酸多态性及其在作物遗传育种中的应用

单核苷酸多态性(single nucleotide polymorphism,SNP)是基因组中最常见的遗传多态性,在遗传学研究的许多方面具有重要的作用.综述了单核苷酸多态性的发现、特点及其应用等方面对植物SNP的研究进展,并展望其在作物遗传育种中的应用前景.     

大规模单核苷酸多态性分析与肿瘤易感性

单核苷酸多态性(SNPs)是人类基因组中最常见的变异形式。作为第三代遗传标记,SNP在基因定位、克隆、遗传多态性方面具有广泛应用,特别是作为基因诊断标记在预防医学中具有十分重要的作用。近年来,随着人类基因组计划的发展,数以百万计的SNP被陆续发现,并可在公共数据库中免费获得。SNP数量的快速增加和SNP检测方法的发展,为其在肿瘤易感性领城的应用提供了可能。在本综述中,我们介绍了几种高通量检测SNP的分析方法,总结了大规模SNP分析技术在肿瘤易感性中的应用,介绍了目前人们对于不同人群中的SNP分析、肿瘤易感基因、个体肿瘤易感性的理解,以及研究SNP标记与肿瘤易感性关系时存在的难点。     

单核苷酸多态性检测技术研究进展

单核苷酸多态性(SNP)是个体中最普遍的遗传变异,主要是指在基因组水平上由单个核苷酸的变异所引起的DNA序列多态性。SNP作为第三代遗传标记,具有遗传稳定性强、数量多、分布广等特点,被广泛应用于群体遗传学、疾病相关基因定位研究中,并在疾病的早期诊断、预防、治疗,研究遗传因素对药物代谢的影响,指导药物临床使用等方面发挥重要的作用。鉴于此,建立适合各级平台应用的准确、高效、稳定的SNP分型技术十分必要。目前SNP检测与分析技术众多,在原理上差别很大,适用范围也不尽相同。本文综述了目前临床应用较广的SNP分型方法,简要介绍了各种技术的检测原理和优缺点,并对SNP分型技术前景进行了展望。     

单核苷酸多态性技术在鸡遗传变异中的研究及应用

单核苷酸多态性(SNP)是继限制性片段长度多态性、微卫星标记之后的第三代分子标记,通常呈双等位基因多态。本文从SNP的特点、SNP的发现与检测、SNP数据库、SNP的频率及其与表型的关系等方面简述了SNP在鸡遗传变异中的研究及应用进展。     

人类基因组中单核苷酸多态性的检测技术

随着人类基因组测序工作的完成,单核苷酸多态性作为继限制性片段长度多态性和微卫星多态性这2种遗传标记之后的第3代遗传标记,已成为人类后基因组时代的主要研究内容之一。系统地介绍了人类基因组中单核苷酸多态性的传统检测方法、新的方法以及基于生物信息学的方法,并对SNP检测技术的发展进行了展望。     

SNP分子标记及其在木本植物遗传育种的应用

木本植物因其生命周期长、基因组杂合度高、基因组较大、遗传背景不清晰等特性,制约了其研究进程。随着现代生物技术的发展,DNA分子标记技术在木本植物研究领域的应用越来越多,其中单核苷酸多态性(SNP)作为第三代分子标记技术以其高效、快速、稳定、可靠等诸多优点得到广泛应用。本文简述SNP标记的特点、开发方法、检测方法及其在木本植物遗传多样性和亲缘关系分析、品种鉴定、连锁图谱构建和辅助育种等方面的研究进展,为更好地应用SNP技术开展木本植物研究提供参考。     

单核苷酸多态性在医学领域的应用

作为第三代DNA遗传标记,单核苷酸多态性(SNP)标记已经成为基因功能研究、寻找疾病基因和基因型鉴定、药物基因组学的主要研究手段,在高危群体的发现、疾病相关基因的鉴定、药物的设计和测试以及分子生物学的基础研究等方面发挥了重要作用。近年来SNP在法医鉴定等领域也有广泛应用。     

基于珙桐SNP位点的dCAPS标记开发

本研究收集了珙桐、喜树等19份植物材料,运用分子生物学和生物信息学手段比对分析了rpoB,rpoC,matK等8个基因碱基序列上的单核苷酸多态性(SNP)位点,在atpF-atpH基因上找到了合适的SNP位点并设计了dCAPS引物,经PCR扩增和酶切验证后,将SNP转化为衍生型酶切扩增多态性序列(dCAPS)标记,可促进SNP标记在珙桐的遗传图谱构建、基因定位、种质资源鉴定、遗传多样性研究等领域的应用。     

单核苷酸多态性及其在水稻中的应用(综述)

单核苷酸多态性(single nucleotide polymorphism,SNP)主要是指基因组的DNA由于单个核苷酸的变异所引起的DNA序列多态性。本文介绍SNP的检测方法及其在水稻中的研究进展和应用。     

基于生物信息学的SNP候选位点搜寻方法

单核苷酸多态性（Single Nucleotide Polymorphism,SNP)是人类基因组中最常见的遗传多态,在遗传学研究的很多方面具有重要的作用。它的搜寻正受到广泛关注。近年来,国际上出现了一种基于生物信息学的发掘SNP新方法,本对方法的两种策略及其各自所存在的问题作一介绍。     

Combined sequence and sequence-structure-based methods for analyzing RAAS gene SNPs: a computational approach

Abstract

The renin–angiotensin–aldosterone system (RAAS) plays a key role in the regulation of blood pressure (BP). Mutations on the genes that encode components of the RAAS have played a significant role in genetic susceptibility to hypertension and have been intensively scrutinized. The identification of such probably causal mutations not only provides insight into the RAAS but may also serve as antihypertensive therapeutic targets and diagnostic markers. The methods for analyzing the SNPs from the huge dataset of SNPs, containing both functional and neutral SNPs is challenging by the experimental approach on every SNPs to determine their biological significance. To explore the functional significance of genetic mutation (SNPs), we adopted combined sequence and sequence-structure-based SNP analysis algorithm. Out of 3864 SNPs reported in dbSNP, we found 108 missense SNPs in the coding region and remaining in the non-coding region. In this study, we are reporting only those SNPs in coding region to be deleterious when three or more tools are predicted to be deleterious and which have high RMSD from the native structure. Based on these analyses, we have identified two SNPs of REN gene, eight SNPs of AGT gene, three SNPs of ACE gene, two SNPs of AT1R gene, three SNPs of CYP11B2 gene and three SNPs of CMA1 gene in the coding region were found to be deleterious. Further this type of study will be helpful in reducing the cost and time for identification of potential SNP and also helpful in selecting potential SNP for experimental study out of SNP pool.     

Functional and genetic survey of all known single-nucleotide polymorphisms within the human deoxyribonuclease I gene in wide-ranging ethnic groups

The single-nucleotide polymorphisms (SNPs) in the human DNase I gene (DNASE1) might be involved in susceptibility to some common diseases; however, only limited population data are available. Further, the effects of these SNPs on in vivo DNase I activity remain unknown. The genotype and haplotype of all the SNPs in DNASE1 were determined in 3 ethnic groups including 14 populations using newly developed methods. Together with our previous data on the nonsynonymous SNPs, two major haplotypes based on the five exonic SNPs were identified; genetic diversity in the Asian population was low. Among 10 SNPs, other than exonic SNPs in the gene, only 3 were polymorphic among all the populations. Haplotype distribution, based on all the polymorphic SNPs, was clarified to be generally varied in an ethnic-dependent manner. Thus, the genetic aspects of DNASE1 with regard to all the SNPs in wide-ranging ethnic groups could be first demonstrated. Further, there was no correlation of all the polymorphic SNPs other than nonsynonymous ones with serum DNase I activity levels. Polymorphic SNPs other than the exonic SNPs might not be directly related to common diseases through alterations in in vivo levels of the activity.     

Haplotype block structure and its applications to association studies: power and study designs

Recent studies have shown that the human genome has a haplotype block structure, such that it can be divided into discrete blocks of limited haplotype diversity. In each block, a small fraction of single-nucleotide polymorphisms (SNPs), referred to as "tag SNPs," can be used to distinguish a large fraction of the haplotypes. These tag SNPs can potentially be extremely useful for association studies, in that it may not be necessary to genotype all SNPs; however, this depends on how much power is lost. Here we develop a simulation study to quantitatively assess the power loss for a variety of study designs, including case-control designs and case-parental control designs. First, a number of data sets containing case-parental or case-control samples are generated on the basis of a disease model. Second, a small fraction of case and control individuals in each data set are genotyped at all the loci, and a dynamic programming algorithm is used to determine the haplotype blocks and the tag SNPs based on the genotypes of the sampled individuals. Third, the statistical power of tests was evaluated on the basis of three kinds of data: (1) all of the SNPs and the corresponding haplotypes, (2) the tag SNPs and the corresponding haplotypes, and (3) the same number of randomly chosen SNPs as the number of tag SNPs and the corresponding haplotypes. We study the power of different association tests with a variety of disease models and block-partitioning criteria. Our study indicates that the genotyping efforts can be significantly reduced by the tag SNPs, without much loss of power. Depending on the specific haplotype block-partitioning algorithm and the disease model, when the identified tag SNPs are only 25% of all the SNPs, the power is reduced by only 4%, on average, compared with a power loss of approximately 12% when the same number of randomly chosen SNPs is used in a two-locus haplotype analysis. When the identified tag SNPs are approximately 14% of all the SNPs, the power is reduced by approximately 9%, compared with a power loss of approximately 21% when the same number of randomly chosen SNPs is used in a two-locus haplotype analysis. Our study also indicates that haplotype-based analysis can be much more powerful than marker-by-marker analysis.     

Genome-wide single nucleotide polymorphism and Insertion-Deletion discovery through next-generation sequencing of reduced representation libraries in common bean

Single nucleotide polymorphisms (SNPs) and insertions-deletions (InDels) are valuable molecular markers for genomics and genetics studies and molecular breeding. The advent of next-generation sequencing techniques has enabled researchers to approach high-throughput and cost-effective SNP and InDel discovery on a genomic scale. In this report, 36 common bean genotypes grown in Canada were used to construct reduced representation libraries for next-generation sequencing. Using 76 million sequence reads generated by the Illumina HiSeq 2000 Sequencing System, we identified a total of 43,698 putative SNPs and 1,267 putative InDels. Of the SNPs, 43,504 were bi-allelic and 194 were tri-allelic, and the InDels comprised 574 insertions and 693 deletions. The putative bi-allelic SNPs were distributed across all 11 chromosomes with the highest number of SNPs observed in chromosome 2 (4,788), and the lowest in chromosome 10 (2,941). With the aid of the recent release of the first chromosome-scale version of Phaseolus vulgaris, 24,907 bi-allelic SNPs, 79 tri-allelic SNPs, 315 insertions, and 377 deletions were located in 8,758, 77, 273, and 364 genes, respectively. Among these 24,907 bi-allelic SNPs, 7,168 nonsynonymous bi-allelic SNPs were identified within 36 common bean genotypes that were located in 4,303 genes. A total of 113 putative SNPs were randomly chosen for validation using high-resolution melt analysis. Of the 113 candidate SNPs, 105 (92.9 %) contained the predicted SNPs.     

Discovery, characterization and validation of single nucleotide polymorphisms within 206 bovine genes that may be considered as candidate genes for beef production and quality

A large number of putative single nucleotide polymorphisms (SNPs) have been identified from the bovine genome-sequencing project. However, few of these have been validated and many will turn out to be sequencing artefacts or have low minor allele frequencies. In addition, there is little information available on SNPs within coding regions, which are likely to be responsible for phenotypic variation. Therefore, additional SNP discovery is necessary to identify and validate polymorphisms both in specific genes and genome-wide. Sequence-tagged sites within 286 genes were resequenced from a panel of animals representing a wide range of European cattle breeds. For 80 genes, no polymorphisms were identified, and 672 putative SNPs were identified within 206 genes. Fifteen European cattle breeds (436 individuals plus available parents) were genotyped with these putative SNPs, and 389 SNPs were confirmed to have minor allele frequencies above 10%. The genes containing SNPs were localized on chromosomes by radiation hybrid mapping and on the bovine genome sequence by Blast . Flanking microsatellite loci were identified, to facilitate the alignment of the genes containing the SNPs in relation to mapped quantitative trait loci. Of the 672 putative SNPs discovered in this work, only 11 were found among the validated SNPs and 100 were found among the approximately 2.3 million putative SNPs currently in dbSNP. The genes studied in this work could be considered as candidates for traits associated with beef production and the SNPs reported will help to assess the role of the genes in the genetic control of muscle development and meat quality. The allele frequency data presented allows the general utility of the SNPs to be assessed.     

人类基因组SNPs的研究现状及应用前景

基因组DNA是生物体各种生理、病理性状的物质基础,人类DNA序列变异约90%表现为单核苷酸多态性(singlenucleotidepolymorphisms,SNPs),这是一种常见的遗传变异类型,在人类基因组中广泛存在,被认为是人类疾病易感性和药物反应的决定性因素。本文主要介绍了SNPs的分类及特点、人类基因组SNPs的研究现状、SNPs在实践中的应用,以及SNPs在遗传作图、医药、遗传易感性、个体化医疗等方面的研究前景,并探讨了当前SNPs研究中存在的问题。     

Development and application of a set of breeder-friendly SNP markers for genetic analyses and molecular breeding of rice (Oryza sativa L.)

Single nucleotide polymorphisms (SNPs) are the most abundant DNA markers in plant genomes. In this study, based on 54,465 SNPs between the genomes of two Indica varieties, Minghui 63 (MH63) and Zhenshan 97 (ZS97) and additional 20,705 SNPs between the MH63 and Nipponbare genomes, we identified and confirmed 1,633 well-distributed SNPs by PCR and Sanger sequencing. From these, a set of 372 SNPs were further selected to analyze the patterns of genetic diversity in 300 representative rice inbred lines from 22 rice growing countries worldwide. Using this set of SNPs, we were able to uncover the well-known Indica-Japonica subspecific differentiation and geographic differentiations within Indica and Japonica. Furthermore, our SNP results revealed some common and contrasting patterns of the haplotype diversity along different rice chromosomes in the Indica and Japonica accessions, which suggest different evolutionary forces possibly acting in specific regions of the rice genome during domestication and evolution of rice. Our results demonstrated that this set of SNPs can be used as anchor SNPs for large scale genotyping in rice molecular breeding research involving Indica-Japonica and Indica-Indica crosses.     

Discovery,validation and characterization of 1039 cattle single nucleotide polymorphisms

We identified ～13 000 putative single nucleotide polymorphisms (SNPs) by comparison of repeat‐masked BAC‐end sequences from the cattle RPCI‐42 BAC library with whole‐genome shotgun contigs of cattle genome assembly Btau 1.0. Genotyping of a subset of these SNPs was performed on a panel containing 186 DNA samples from 18 cattle breeds including 43 trios. Of 1039 SNPs confirmed as polymorphic in the panel, 998 had minor allele frequency ≥0.25 among unrelated individuals of at least one breed. When Btau 4.0 became available, 974 of these validated SNPs were assigned in silico to known cattle chromosomes, while 41 SNPs were mapped to unassigned sequence scaffolds, yielding one SNP every ～3 Mbp on average. Twenty‐four SNPs identified in Btau 1.0 were not mapped to Btau 4.0. Of the 1015 SNPs mapped to Btau 4.0, 959 SNPs had nucleotide bases identical in Btau 4.0 and Btau 1.0 contigs, whereas 56 bases were changed, resulting in the loss of the in silico SNP in Btau 4.0. Because these 1039 SNPs were all directly confirmed by genotyping on the multi‐breed panel, it is likely that the original polymorphisms were correctly identified. The 1039 validated SNPs identified in this study represent a new and useful resource for genome‐wide association studies and applications in animal breeding.     

Ethnic differences in the linkage disequilibrium and distribution of single-nucleotide polymorphisms in 35 candidate genes for cardiovascular diseases

Single-nucleotide polymorphisms (SNPs) are commonly used to study genetics for common diseases and predict pharmacological response. The selection of likely informative SNPs in association studies depends on their allele frequencies and on the linkage disequilibrium (LD) between SNPs, both of which may show interethnic differences. Among three populations consisting of 207 Chinese, 858 French, and 395 Spanish, we compared the allele frequency distributions of 64 intragenic SNPs of 35 candidate genes for cardiovascular diseases. Twenty-eight of these SNPs from 12 genes were also examined for intragenic LD. About 20% of SNPs were restricted to Europeans, being monomorphic in Chinese, among them mostly nonsynonymous coding SNPs and noncoding SNPs. Only 1.6% of SNPs were specific in Chinese, commensurate with the detection of these SNPs almost exclusively in Caucasians. Similarly, these SNPs were more often rare (<0.1 minor allele frequency) in Chinese (44.3%) than in Europeans (31.1%). The variant allele frequencies and intermarker LDs in terms of D' and Delta(2) were highly correlated between French and Spanish populations (r = 0.98-0.99, p < 0.001). However, only moderate correlations of allele frequencies and D' were found between the Chinese and the European populations (r = 0.7 and 0.3, respectively) despite a high correlation of Delta(2) values (r = 0.8). These results suggest that ethnic considerations are important in the selection of SNPs for association studies of candidate genes, as this may affect the power of the study as well as the likelihood of asking relevant questions and getting medically meaningful answers.