医学信息分析-Chapter-1-Next-Generation-DNA-Sequencing-Methods

1、Next-Generation DNA Sequencing MethodsChapter 1Q1给你一段DNA序列，你想要什么样的DNA序列？如果你有了一段DNA序列，你会干什么？不同的专业如果瞬间给你百万数量级的DNA序列，你又会如何？请你考虑如果我们能够检测出某一细胞里所有的DNA序列，是不是意味着我们已经能够破解该细胞的绝大多数分子机制？如果不是，我们还需要什么才有能。Sanger SequencingRoche 454Sample Input & FragmentationLibrary PreparationOne Fragment = One BeademPCR: Emulsio

2、n PCR AmplificationSequencing: One Bead = One ReadPyrosequencing chemistrySingle-nucleotide addition: pyrosequencingFeaturesHowever, the calibrated base calling cannot properly interpret long stretches (6) of the same nucleotide (homopolymer run), so these areas are prone to base insertion and delet

3、ion errors during base calling. By contrast, because each incorporation step is nucleotide specific, substitution errors are rarely encountered in Roche/454 sequence reads.The FLX instrument currently provides 100 flows of each nucleotide during an 8-h run, which produces an average read length of 2

4、50 nucleotides (an average of 2.5 bases per flow are incorporated).mixed sequences (more than one initial DNA fragment per bead)FeaturesAlthough shorter than reads derived from capillary sequencers, FLXreads are of sufficient length to assemble small genomes such as bacterial and viral genomes to hi

5、gh quality and contiguity.Preprocessvarious quality filters to remove poor-quality sequencesmixed sequences (more than one initial DNA fragment per bead)sequences without the initiating TCGA sequence.P11）设计一个程序 随机的产生1000bp的DNA序列2）并随机的从中取出1000个25bp的序列，记住位置3）开发一个函数用于比对这1000个25bp到原来的1000bp的DNA序列，计算出相对位

6、置，并与原来的产生位置相比较，看是否一致4）给出程序流程图，及其计算时间以及相应的计算机配置Illumina/Solexa Genome AnalyzerCyclic reversible termination.FeaturesSubstitutions are the most common error type, with a higher portion of errors occurring when the previous incorporated nucleotide is a G baseGenome analysis of Illumina/Solexa data has

7、revealed an underrepresentation of AT-rich and GC-rich regions, which is probably due to amplification bias during template preparation.Sequence variants are called by aligning reads to a reference genome using bioinformatics tools such as MAQ or ELAND. Bentley and colleagues reported high concordan

8、ce (99.5%) of single-nucleotide variant (SNV) calls with standard genotyping arrays using both alignment tools, and a false-positive rate of 2.5% with novel SNVs. Other reports have described a higher falsepositive rate associated with novel SNV detection using these alignment toolsApplied Biosystem

9、s SOLiDSequencerSequencing by ligationFeaturesThe method uses two-base-encoded probes, which has the primary advantage of improved accuracy in colour calling and SNV calling, the latter of which requires an adjacent valid colour change.Substitutions are the most common error type. Similar to the gen

10、ome analysis of Illumina/Solexa reads, SOLiD data have also revealed an underrepresentation of AT-rich and GC-rich regions.P2在先前的例子中，随机的在25bp的序列上进行1/2/3次碱基的改变检查是否先前的比对代码可以用于寻找出定位，如不行，请设计有效的解决方案。（如果随机的在25bp的序列上进行1/2/3次碱基的删除或者添加，检查是否先前的比对代码可以用于寻找出定位，如不行，请设计有效的解决方案。）In summary-KeysThe length of a seque

11、nce read from all current next generation platforms is much shorter than that from a capillary sequencereach next generation read type has a unique error model different from that already established for capillary sequence reads.in strain-to-reference comparisons (resequencing), the typical definiti

12、on of repeat content must be revised in the context of the shorter read length.a much higher read coverage or sampling depth is required for comprehensive resequencing with short reads to adequately cover the reference sequence at the depth and low gap size needed.In summaryimage analysis, signal pr

13、ocessing, background subtraction, base calling, and quality assessment to produce the final sequence reads for each rmation technology (IT), computational, data storage, and laboratory information management system (LIMS) infrastructuresIn summaryAlthough quality scores and accuracy estimate

14、s are provided by each manufacturer, there is no consensus that a quality base from one platform is equivalent to that from another platform.more importantly, these methods do not require PCR, which creates mutations in clonally amplified templates that masquerade as sequence variants. AT-rich and G

15、C-rich target sequences may also show amplification bias in product yield. In summarydemand on the efficiency of the addition process, and incomplete extension of the template ensemble results in lagging-strand dephasing. Signal dephasing increases fluorescence noise, causing base-calling errors and

16、 shorter readsIn summarySingle molecules, however, are susceptible to multiple nucleotide or probe additions in any given cycle. Here, deletion errors will occur owing to quenching effects between adjacent dye molecules or no signal will be detected because of the incorporation of dark nucleotides o

17、r probes.Dark nucleotides or probes A nucleotide or probe that does not contain a fluorescent label. It can be generated from its cleavage and carry-over from the previous cycle or be hydrolysed in situ from its dye-labelled counterpart in the current cycle.In summaryreported that deletion errors in

18、 homopolymeric repeat regions were the most common error type (5% frequency) when using the primer-immobilized strategy. This is likely to be related to the incorporation of two or more Cy5-12ss-dNTPs in a given cycle. These errors can be greatly reduced with two-pass sequencing, which provides 25-b

19、ase consensus reads using the template-immobilized strategy.direct RNA sequencing, as it sequences RNA templates directly without the need to convert them into cDNAsReal-time sequencingFeaturesTo assess the accuracy of this method, a four-colour sequencing experiment was conducted using a known 150

20、bp linear template. Base calls from the real-time reads were determined from their corresponding fluorescence pulses. when the reads were compared to a known sequence, 27 errors consisting of deletions, insertions and mismatches were identified, corresponding to a read accuracy of approximately 83%

21、(131/158).FeaturesGiven that most errors appear as stochastic events, the authors showed that repeated sequencing of the same template molecule 15 times or more could improve the consensus read accuracy to 99%.At the 2009 AGBT meeting, Pacific Biosciences reported improvements to their platform; whe

22、n it was used to sequence the E. coli genome at 38-fold base coverage, 99.3% genome coverage was obtained. The onsensus accuracy reached was 99.999% for the entire genome, with read lengths averaging 964 basesGenome enrichmentuse NGS platforms to target specific regions of interestThis strategy can be used to examine all of the exons in the genome, specific gene families that constitute known drug targets or megabasesize regions that are implicated in disease or pharmacogenetics effects through genome-wide association studiesSumma