Landscape of next-generation sequencing technologies.
Landscape of next-generation sequencing technologies.
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DOI：
10.1021/ac2010857
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发表时间：
2011-06-15
影响因子：
7.4
通讯作者：
Barron, Annelise E.
中科院分区：
文献类型：
--
作者：
Niedringhaus, Thomas P.;Milanova, Denitsa;Kerby, Matthew B.;Snyder, Michael P.;Barron, Annelise E.
DNA测序正处于一场巨大的技术转变的阵痛中，其显著特征是产量大幅增加，原始序列的单位碱基成本急剧下降，同时为了利用这项技术，需要对大型资本设备进行大量投资。就在几年前，对大多数人来说还是遥不可及的奢侈品(个人基因组测序、元基因组学研究，以及无数感兴趣的生物体的测序)正在以快速的速度越来越多地成为可能。这篇综述集中在第三代和第四代测序方法背后的技术：它们的挑战、当前的限制和诱人的前景。第一代测序包括由Sanger和Coulson1在1975年开创的链终止方法，或Maxam和Gilbert在1976±1977年开创的化学方法。1977年，桑格测序了第一个基因组，噬菌体ΦX174，全长5,375个碱基。3这些方法及其早期历史4以前已经详细回顾过了。5四色荧光Sanger测序，其中每种颜色对应于四个DNA碱基中的一个，是由应用生物系统公司和Beckman Coulter公司销售的自动毛细管电泳(CE)系统使用的方法，该应用生物系统公司现已整合到Life Technologies中(表1)。6 2001年报告的第一个复合人类基因组序列主要是用毛细管电泳法获得的，花费巨大，并在十多年的时间里付出了巨大的人力物力。7、8虽然2001年报告的基因组是一项正在进行的工作，但不断改进的“参考”基因组的可获得性是正在进行的生物科学变革的基础，并且仍然是研究基因表型关系的基础。考虑到到目前为止文献中已经出现(和没有出现)的报告，很可能对复杂疾病有医学意义(可操作)的洞察将需要额外类型的“个人”基因组数据，例如，特定组织的mRNA表达谱和mRNA测序，基因调节区的个性化分析，表观遗传学谱，以及高质量的远程染色体图谱，以编目重大的缺失、插入、重排等。这些整合的基因组数据集与数百或数千个人的全面病史的相关性可能是进入个性化医学时代所需要的。9？11个大型测序中心现已完成向下一代测序仪的转换；联合基因组研究所(JGI)已经淘汰了所有桑格测序仪。12在另一个极端，在小规模的下一代测序仪在每准确碱基的成本以及读取长度上超过CE之前，CE系统可能仍将大量用于台式规模的定向测序，如定量基因表达、生物标记物识别和路径分析。
DNA sequencing is in the throes of an enormous technolog-ical shift marked by dramatic throughput increases, a precipitously dropping per-base cost of raw sequence, and an accompanying requirement for substantial investment in large capital equipment in order to utilize the technology. Investigations that were, for most, unreachable luxuries just a few years ago (individual genome sequencing, metagenomics studies, and the sequencing of myriad organisms of interest) are being increasingly enabled, at a rapid pace. This Review concentrates on the technology behind the third-and fourth-generation sequencing methods: their challenges, current limitations, and tantalizing promise. First-generation sequencing encompasses the chain termination method pioneered by Sanger and Coulson1 in 1975 or the chemical method of Maxam and Gilbert in 1976À1977. 2 In 1977, Sanger sequenced the first genome, bacteriophage ΦX 174, which is 5375 bases in length. 3 These methods and their early history4 have been reviewed in detail previously. 5 Four-color fluorescent Sanger sequencing, where each color corresponds to one of the four DNA bases, is the method used by the automated capillary electrophoresis (CE) systems marketed by Applied Biosystems Inc., now integrated into Life Technologies, and by Beckman Coulter Inc.(Table 1). 6 The first composite human genome sequence, reported in 2001, was obtained largely using CE, at great cost and with intense human effort over more than a decade. 7, 8 While the genome reported in 2001 was a work in progress, the availability of an ever-improving “reference” genome is the basis of an ongoing transformation of biological science and remains fundamental to investigations of genotypeÀ phenotype relationships. Considering reports that have appeared (and not appeared) in the literature to date, it could well be that medically meaningful (actionable) insights into complex diseases will require additional types of “personal” genomic data, for instance, tissue-specific mRNA expression profiling and mRNA sequencing, individualized analysis of gene regulatory regions, epigenetic profiling, and high-quality, long-range chromosome mapping to catalog significant deletions, insertions, rearrangements, etc. Correlation of such integrated genomic data sets with comprehensive medical histories for hundreds or thousands of individuals may be what it takes to reach an era of personalized medicine. 9À11 Large-scale sequencing centers are now completing the conversion to nextgeneration sequencers; the Joint Genome Institute (JGI) has retired all of their Sanger sequencing instruments. 12 At the other extreme, until small-scale next-generation sequencers can outperform CE on a cost per accurate base called as well as read length, CE systems will likely remain in heavy use for benchtop-scale, targeted sequencing for directed investigations such as quantitative gene expression, biomarker identification, and pathway analysis.
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影响因子：
48
作者：
Flusberg, Benjamin A.;Webster, Dale R.;Lee, Jessica H.;Travers, Kevin J.;Olivares, Eric C.;Clark, Tyson A.;Korlach, Jonas;Turner, Stephen W.
通讯作者：
Turner, Stephen W.
影响因子：
3.2
作者：
Esfandyarpour, Hesaam;Zheng, Bo;Davis, Ronald W.
通讯作者：
Davis, Ronald W.
影响因子：
56.9
作者：
Armbrust, EV;Berges, JA;Rokhsar, DS
通讯作者：
Rokhsar, DS
影响因子：
10.8
作者：
Fologea, D;Gershow, M;Li, JL
通讯作者：
Li, JL
影响因子：
46.9
作者：
Drmanac, S;Kita, D;Drmanac, R
通讯作者：
Drmanac, R