基因组拷贝数变异研究进展

基因组结构变异分为两个层次:显微水平(microscopic)和亚显微水平(submicroscopic)。显微水平的基因组结构变异主要是指显微镜下可见的染色体畸变,包括整倍体或非整倍体、缺失、插入、倒位、易位、脆性位点等结构变异。亚显微水平的基因组结构变异是指DNA片段长度在1Kb-3Mb的基因组结构变异,包括缺失、插入、重复、重排、倒位、DNA拷贝数目变化(copy numbervariation,CNV),这些统称为CNV或者CNP(copy number polymorphisms,CNP)。对CNV的研究能够帮助研究者建立遗传检测假说,进而发现疾病易感基因,同时加深对表型变异的理解,为今后研究人类生物功能、进化、疾病奠定基础。本文主要从CNV的研究历史、分子机制、研究方法、研究意义等四个方面进行综述.。     

拷贝数变异: 基因组多样性的新形式

基因拷贝数变异是指DNA片段大小范围从kb到Mb的亚微观突变, 是一可能具有致病性、良性或未知临床意义的基因组改变。Fosmid末端配对序列比较策略、比较基因组杂交芯片是当前较多使用的检测手段。染色体非等位的同源重排、非同源突变和非b DNA结构是造成基因组拷贝数变异的重要原因。拷贝数变异可导致不同程度的基因表达差异, 对正常表型的构成及疾病的发生发展具有一定作用。文章在总结基因拷贝数变异的认识过程和研究策略的基础上, 分析了拷贝数变异的形成和作用机制, 介绍了第一代人类基因组拷贝数变异图谱, 阐述了拷贝数变异研究的临床意义, 提示在探索疾病相关的遗传变异时不能错失拷贝数变异这一基因组多样性的新形式。     

拷贝数变异的全基因组关联分析

基因组拷贝数变异(copy number variations,CNVs)是指与基因组参考序列相比,基因组中≥1 kb的DNA片段插入、缺失和/或扩增,及其互相组合衍生出的复杂变异．由于其具有分布范围广、可遗传、相对稳定和高度异质性等特点,目前认为,CNVs是一种新的可以作为疾病易感标志的基因组DNA多态性,其变异引起的基因剂量改变可以导致表型改变．最近,一种基于CNVs的新的疾病易感基因鉴定策略——CNV全基因组关联分析开始出现,这一策略和传统的基于单核苷酸多态性的关联分析具有互补性,通过认识基因组结构变异可以认识复杂疾病的分子机制和遗传基础．     

人类基因组结构变异检测研究进展

高通量、高分辨率基因组学技术的出现推动了人类基因组中长度在1kb～3Mb的亚显微水平结构变异检测方法的发展,这些结构变异主要包括基因拷贝数变异、倒置、插入、缺失、重复及其他基因重排．而传统的细胞遗传学技术达不到如此高的分辨率．本文介绍了目前主要的基因组结构变异的检测技术,包括基于芯片的比较基因组杂交技术和代表性寡核苷酸芯片分析技术,基于PCR的多重扩增探针杂交技术和依赖于连接反应的多重探针扩增技术,配对末端图谱技术等．还比较和分析了各种方法的优劣势并提出了目前结构变异数据库存在的问题．最后讨论了这些变异对于人类表型多态性、疾病易感性、药物反应程度及群体遗传学的影响．     

合成型酵母基因组重排技术

基因组的结构变异是生物体表型进化的重要驱动力之一。设计与合成酵母基因组为人工基因组结构变异提供了新途径。人工合成酿酒酵母基因组(Sc2.0)通过系统性地引入重排元件,赋予了基因组柔性可变的功能,可诱导产生 DNA 片段的删除、反转、复制、移位等基因组结构变异。合成型酵母基因组重排技术可实现菌株性状的快速进化,并且为研究基因组结构变异与表型变化间的关系提供了一种快速、全新的方法。综述了合成型酵母基因组重排技术的研究热点和技术进展,并展示了其在创新菌种中的应用价值。     

牛疾病相关基因的DNA变异及遗传控制

牛基因组中一些重要基因的DNA突变通过改变基因的表达和蛋白质功能来影响机体对疾病的抗性或易感性。控制牛疾病的DNA变异主要分为单基因座及多基因座两类。导致疾病的单基因座类型亦称因果突变,其遗传基础较简单,突变一般位于基因编码区或非编码区,多为单碱基或少数几个碱基的突变,这些突变导致氨基酸的错义突变、翻译提前终止或部分外显子缺失等。相比而言,多基因相关疾病的遗传基础较为复杂,遗传-病原体-环境间的互作是导致这类复杂疾病的主要原因。文章综述了由单基因座和多基因座遗传变异所控制的牛主要疾病的研究和应用现状,以及在牛育种及生产中为降低这些疾病的发生所采用的遗传控制策略。     

基因组拷贝数变异及其突变机理与人类疾病

拷贝数变异(Copy number variation,CNV)是由基因组发生重排而导致的,一般指长度为1 kb以上的基因组大片段的拷贝数增加或者减少,主要表现为亚显微水平的缺失和重复。CNV是基因组结构变异(Structural variation,SV)的重要组成部分。CNV位点的突变率远高于SNP(Single nucleotide polymorphism),是人类疾病的重要致病因素之一。目前,用来进行全基因组范围的CNV研究的方法有:基于芯片的比较基因组杂交技术(array-based comparative genomic hybridization,aCGH)、SNP分型芯片技术和新一代测序技术。CNV的形成机制有多种,并可分为DNA重组和DNA错误复制两大类。CNV可以导致呈孟德尔遗传的单基因病与罕见疾病,同时与复杂疾病也相关。其致病的可能机制有基因剂量效应、基因断裂、基因融合和位置效应等。对CNV的深入研究,可以使我们对人类基因组的构成、个体间的遗传差异、以及遗传致病因素有新的认识。     

高压导致水稻变异品系发生DNA甲基化模式及基因组结构的改变

用高压力诱变水稻品种“毕粳38”, 产生了两个稳定的变异: 变异1与变异2. 对原种及两个变异品系的基因组DNA及Hpa Ⅱ/Msp Ⅰ酶切后的基因组DNA采用ISSR及RAPD分析; 并通过特异引物分析水稻的转座子mPing的变化; 且对变异片段纯化测序; 同时以水稻基因组中潜在活跃的反转录转座子LTR(long terminal repeat)Osr7, Osr36, Tos19(Osr54)以及转座子MITEs(miniature inverted-repeat transposable elements)的mPing和Pong及某些特异片段为探针, 进行Southern杂交. 结果显示原种及两个变异品系不仅存在着基因组结构的变异, 而且发生了DNA甲基化模式的改变. 此外, 对原种及两个变异品系进行了异地栽种, 其形态水平的变异稳定表达. 结果表明: 高静水压对高等植物的种子进行诱变, 产生表型变异的分子基础是由于发生了DNA分子水平上的广泛变异, 并证明高压可导致水稻多种转座元件的可能激活及DNA甲基化模式的改变. 因此可以认为高压是引起植物遗传变异一个重要因素, 可能在作物诱变育种中具有广阔的应用前景.     

几种转基因植物体细胞克隆变异的多样性研究

分析了杨树、水稻和甘蔗转基因植株体细胞克隆的表型变异和基因组DNA多态性。探讨了以下问题:转基因植株体细胞克隆的1)表型多样性, 2)基因组DNA多样性, 3)二者的相关性, 4)表型变异和DNA变异的可遗传特性, 5)产生的可能原因,以及6)在农业生产上的应用。     

与疾病相关的非同义单核苷酸多态性预测的研究进展

单核苷酸多态性(single nucleotide polymorphism,SNPs),即在基因组水平上由单个核苷酸的变异而引起的DNA序列多态性变化,具体是指在DNA序列中的单个碱基的变异,其是人类基因组变异种最常见的一种。SNP研究最主要的目的就是对人类表型变异遗传学的理解,尤其是关于人类遗传疾病的研究。而非同义单核苷酸多态性(nsSNPs)是SNPs中的一种,主要是指处于编码区会引起翻译后对应氨基酸序列变化的单核苷酸突变。因为nsSNPs可能会对蛋白质的功能造成影响,被认为是造成人类遗传病的主要原因。因此将与疾病相关的nsSNPs从中性的nsSNPs中区分出来是很重要的。本文根据国内外与疾病相关nsSNPs预测的研究,分析了预测中所涉及到的特征属性,总结了对这些特征进行优化的特征选择方法,并概述了在预测过程中使用的各种分类器。     

The role of structural genomic variants in population differentiation and ecotype formation in Timema cristinae walking sticks

Theory predicts that structural genomic variants such as inversions can promote adaptive diversification and speciation. Despite increasing empirical evidence that adaptive divergence can be triggered by one or a few large inversions, the degree to which widespread genomic regions under divergent selection are associated with structural variants remains unclear. Here we test for an association between structural variants and genomic regions that underlie parallel host‐plant‐associated ecotype formation in Timema cristinae stick insects. Using mate‐pair resequencing of 20 new whole genomes we find that moderately sized structural variants such as inversions, deletions and duplications are widespread across the genome, being retained as standing variation within and among populations. Using 160 previously published, standard‐orientation whole genome sequences we find little to no evidence that the DNA sequences within inversions exhibit accentuated differentiation between ecotypes. In contrast, a formerly described large region of reduced recombination that harbours genes controlling colour‐pattern exhibits evidence for accentuated differentiation between ecotypes, which is consistent with differences in the frequency of colour‐pattern morphs between host‐associated ecotypes. Our results suggest that some types of structural variants (e.g., large inversions) are more likely to underlie adaptive divergence than others, and that structural variants are not required for subtle yet genome‐wide genetic differentiation with gene flow.     

Assessing cell-specific effects of genetic variations using tRNA microarrays

Background

Short-read resequencing of genomes produces abundant information of the genetic variation of individuals. Due to their numerous nature, these variants are rarely exhaustively validated. Furthermore, low levels of undetected variant miscalling will have a systematic and disproportionate impact on the interpretation of individual genome sequence information, especially should these also be carried through into in reference databases of genomic variation.

Results

We find that sequence variation from short-read sequence data is subject to recurrent-yet-intermittent miscalling that occurs in a sequence intrinsic manner and is very sensitive to sequence read length. The miscalls arise from difficulties aligning short reads to redundant genomic regions, where the rate of sequencing error approaches the sequence diversity between redundant regions. We find the resultant miscalled variants to be sensitive to small sequence variations between genomes, and thereby are often intrinsic to an individual, pedigree, strain or human ethnic group. In human exome sequences, we identify 2–300 recurrent false positive variants per individual, almost all of which are present in public databases of human genomic variation. From the exomes of non-reference strains of inbred mice, we identify 3–5000 recurrent false positive variants per mouse – the number of which increasing with greater distance between an individual mouse strain and the reference C57BL6 mouse genome. We show that recurrently miscalled variants may be reproduced for a given genome from repeated simulation rounds of read resampling, realignment and recalling. As such, it is possible to identify more than two-thirds of false positive variation from only ten rounds of simulation.

Conclusion

Identification and removal of recurrent false positive variants from specific individual variant sets will improve overall data quality. Variant miscalls arising are highly sequence intrinsic and are often specific to an individual, pedigree or ethnicity. Further, read length is a strong determinant of whether given false variants will be called for any given genome – which has profound significance for cohort studies that pool datasets collected and sequenced at different points in time.

     

Chapter 6: Structural Variation and Medical Genomics

Differences between individual human genomes, or between human and cancer genomes, range in scale from single nucleotide variants (SNVs) through intermediate and large-scale duplications, deletions, and rearrangements of genomic segments. The latter class, called structural variants (SVs), have received considerable attention in the past several years as they are a previously under appreciated source of variation in human genomes. Much of this recent attention is the result of the availability of higher-resolution technologies for measuring these variants, including both microarray-based techniques, and more recently, high-throughput DNA sequencing. We describe the genomic technologies and computational techniques currently used to measure SVs, focusing on applications in human and cancer genomics.

What to Learn in This Chapter

• Current knowledge about the prevalence of structural variation in human and cancer genomes.
• Strategies for using microarray and high-throughput DNA sequencing technologies to measure structural variation.
• Computational techniques to detect structural variants from DNA sequencing data.

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

Potenzial und Herausforderungen der personalisierten Genomik und des 1000-Genom-Projekts

The ability to sequence entire individual human genomes has heralded a new era in human genetics. Such advances in sequencing technologies make it possible to address new questions such as the generation of a comprehensive map of common and rare genetic variants in humans. The 1000 Genome Project will analyze 2500 genomes and is expected to greatly expand our knowledge about genomic variation, both on single nucleotide polymorphisms and genomic structural variants in a number of human ethnic populations. Furthermore, the possibility to use these new sequencing technologies for such large scale projects will be evaluated. Finally, new bioinformatics solutions will be developed to efficiently store and process such large volumes of data for the scientific community. This catalogue of common and rare variations will facilitate the development of better methods for phenotype-genotype associations and help uncover the molecular bases for a variety of diseases in the near future.     

Using de novo assembly to identify structural variation of eight complex immune system gene regions

Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14⁺ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data. Continued reductions in the cost of these technologies will enable application of these methods to larger samples and provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.     

Standing genomic variation within coding and regulatory regions contributes to the adaptive capacity to climate in a foundation tree species

Global climate is rapidly changing, and the ability for tree species to adapt is dependent on standing genomic variation; however, the distribution and abundance of functional and adaptive variants are poorly understood in natural systems. We test key hypotheses regarding the genetics of adaptive variation in a foundation tree: genomic variation is associated with climate, and genomic variation is more likely to be associated with temperature than precipitation or aridity. To test these hypotheses, we used 9,593 independent, genomic single‐nucleotide polymorphisms (SNPs) from 270 individuals sampled from Corymbia calophylla's entire distribution in south‐western Western Australia, spanning orthogonal temperature and precipitation gradients. Environmental association analyses returned 537 unique SNPs putatively adaptive to climate. We identified SNPs associated with climatic variation (i.e., temperature [458], precipitation [75] and aridity [78]) across the landscape. Of these, 78 SNPs were nonsynonymous (NS), while 26 SNPs were found within gene regulatory regions. The NS and regulatory candidate SNPs associated with temperature explained more deviance (27.35%) than precipitation (5.93%) and aridity (4.77%), suggesting that temperature provides stronger adaptive signals than precipitation. Genes associated with adaptive variants include functions important in stress responses to temperature and precipitation. Patterns of allelic turnover of NS and regulatory SNPs show small patterns of change through climate space with the exception of an aldehyde dehydrogenase gene variant with 80% allelic turnover with temperature. Together, these findings provide evidence for the presence of adaptive variation to climate in a foundation species and provide critical information to guide adaptive management practices.     

The genomic pool of standing structural variation outnumbers single nucleotide polymorphism by threefold in the marine teleost Chrysophrys auratus

Recent studies have highlighted an important role of structural variation (SV) in ecological and evolutionary processes, but few have studied nonmodel species in the wild. As part of our long‐term research programme on the nonmodel teleost fish Australasian snapper (Chrysophrys auratus), we aim to build one of the first catalogues of genomic variants (SNPs and indels, and deletions, duplications and inversions) in fishes and evaluate overlap of genomic variants with regions under putative selection (Tajima's D and π), and coding sequences (genes). For this, we analysed six males and six females from three locations in New Zealand and generated a high‐resolution genomic variation catalogue. We characterized 20,385 SVs and found they intersected with almost a third of all annotated genes. Together with small indels, SVs account for three times more variation in the genome in terms of bases affected compared to SNPs. We found that a sizeable portion of detected SVs was in the upper and lower genomic regions of Tajima's D and π, indicating that some of these have an effect on the phenotype. Together, these results shed light on the often neglected genomic variation that is produced by SVs and highlights the need to go beyond the mere measure of SNPs when investigating evolutionary processes, such as species diversification and adaptation.     

Development of a genotype‐by‐sequencing immunogenetic assay as exemplified by screening for variation in red fox with and without endemic rabies exposure

Pathogens are recognized as major drivers of local adaptation in wildlife systems. By determining which gene variants are favored in local interactions among populations with and without disease, spatially explicit adaptive responses to pathogens can be elucidated. Much of our current understanding of host responses to disease comes from a small number of genes associated with an immune response. High‐throughput sequencing (HTS) technologies, such as genotype‐by‐sequencing (GBS), facilitate expanded explorations of genomic variation among populations. Hybridization‐based GBS techniques can be leveraged in systems not well characterized for specific variants associated with disease outcome to “capture” specific genes and regulatory regions known to influence expression and disease outcome. We developed a multiplexed, sequence capture assay for red foxes to simultaneously assess ~300‐kbp of genomic sequence from 116 adaptive, intrinsic, and innate immunity genes of predicted adaptive significance and their putative upstream regulatory regions along with 23 neutral microsatellite regions to control for demographic effects. The assay was applied to 45 fox DNA samples from Alaska, where three arctic rabies strains are geographically restricted and endemic to coastal tundra regions, yet absent from the boreal interior. The assay provided 61.5% on‐target enrichment with relatively even sequence coverage across all targeted loci and samples (mean = 50×), which allowed us to elucidate genetic variation across introns, exons, and potential regulatory regions (4,819 SNPs). Challenges remained in accurately describing microsatellite variation using this technique; however, longer‐read HTS technologies should overcome these issues. We used these data to conduct preliminary analyses and detected genetic structure in a subset of red fox immune‐related genes between regions with and without endemic arctic rabies. This assay provides a template to assess immunogenetic variation in wildlife disease systems.