二代测序技术评估：针对人群靶向测序研究

需积分: 9 118 浏览量更新于2024-09-19 收藏 3.81MB PDF 举报

"这篇文章是关于对下一代测序(Next Generation Sequencing, NGS)平台的评估，特别是针对454、GA、SOLiD这三种技术在群体目标测序研究中的对比分析。发表在Genome Biology 2009年的第10卷第3期，文章编号R32，由Harismendy等人撰写。" 文章深入探讨了在人口规模的目标测序研究中，新一代测序技术的性能和适用性。下一代测序技术，包括454 Life Sciences、Illumina Genome Analyzer (GA)和Applied Biosystems SOLiD系统，这些技术在生物医学研究中发挥了重要作用，使得大规模基因组分析成为可能。首先，454测序技术以其长读长和高覆盖度而著称，尤其适合于组装复杂基因组和检测长序列变异。然而，它的错误率相对较高，且测序成本相对于其他技术来说也较高。相比之下，Illumina GA平台以其高通量和较低的错误率而受到青睐。其短读长的优势在于可以快速处理大量数据，适合于寻找SNPs（单核苷酸多态性）和进行基因表达分析。然而，对于长片段的重组或结构变异的检测可能存在挑战。 SOLiD系统则采用了颜色空间测序，提供了中等长度的读长和较高的碱基分辨率，这有助于提高序列比对的准确性。但是，SOLiD的数据处理和分析流程相对复杂，需要特定的算法来解析颜色编码的信息。在群体遗传学研究中，这些技术的选择取决于研究目标和资源。例如，如果研究侧重于全基因组组装或长链变异，454可能更合适；而如果关注SNP发现或转录组分析，Illumina GA可能更为经济有效；SOLiD可能在需要更高精度的序列比对时更有优势。文章还讨论了这些技术在处理大量样本时的效率和成本效益，以及它们如何影响下游的数据分析和生物信息学工作流程。通过实验比较和模拟分析，作者提供了选择合适测序平台的实用指南，帮助研究者根据项目需求做出决策。总体而言，这篇研究强调了在进行大规模人群测序时，对不同NGS平台的全面理解和评估至关重要，因为每个平台都有其独特的优势和局限性。选择合适的测序技术不仅可以优化研究结果，还可以有效地利用有限的科研经费。

http://genomebiology.com/2009/10/3/R32 Genome Biology 2009, Volume 10, Issue 3, Article R32 Harismendy et al. R32.3

Genome Biology 2009, 10:R32

sequence coverage and for systematic biases giving rise to low

coverage. We show that each NGS platform generates its own

unique pattern of biased sequence coverage that is consistent

between samples. For the short-read platforms, low coverage

intervals tend to be in AT-rich repetitive sequences. We also

performed a comparative analysis with sequence generated

by the well-established ABI Sanger platform (Figure 1) to

determine base calling accuracies and how average fold

sequence coverage impacts base calling errors. Although the

three NGS technologies correctly identify >95% of variant

alleles, the average sequence coverage required to achieve

this performance is greater than the targeted levels of most

current studies.

Results

Generation and alignment of sequence reads to

targeted intervals

The targeted sequence was amplified in the four DNA sam-

ples using long-range PCR (LR-PCR) reactions that were

combined in equimolar amounts and sequenced using the

three NGS technologies (Figure 1). For the Roche 454 plat-

form we obtained an average of 49,000 reads per sample with

an average length of 245 bp (Supplemental Table 1 in Addi-

tional data file 1), using Illumina GA we generated an average

of 5.9 million reads each 36 bases in length per sample, and

using ABI SOLiD we obtained an average of 19.7 million reads

each 35 bases in length per sample. Thus, the amount of

sequence data generated and analyzed was dependent on the

NGS platform and the fraction of the run that was utilized.

The NGS technologies generate a large amount of sequence

but, for the platforms that produce short-sequence reads,

greater than half of this sequence is not usable. On average,

55% of the Illumina GA reads pass quality filters, of which

approximately 77% align to the reference sequence (Supple-

mental Table 1 in Additional data file 1; Additional data file 2).

For ABI SOLiD, approximately 35% of the reads pass quality

filters, and subsequently 96% of the filtered reads align to the

reference sequence. Thus, only 43% and 34% of the Illumina

GA and ABI SOLiD raw reads, respectively, are usable. In con-

trast to the platforms generating short-read lengths, approxi-

mately 95% of the Roche 454 reads uniquely align to the

target sequence. When designing experiments and calculat-

ing the target coverage for a region, one must consider the

fraction of alignable sequence.

Overrepresentation of amplicon end sequences

In examining the distribution of mapped reads, we observed

that the sequences corresponding to the 50 bp at the ends and

the overlapping intervals of the amplicons have extremely

high coverage (Figure 2; Additional data file 2). These

regions, representing about 2.3% (approximately 6 kb) of the

targeted intervals, account for up to 56% of the sequenced

base pairs for Illumina GA technology. This extreme sequence

coverage bias results from overrepresentation of the ampli-

con ends in the DNA samples after fragmentation prior to

library generation. For the ABI SOLiD platform an amplicon

end depletion protocol was employed to remove the overrep-

resented amplicon ends; this was partially successful and

resulted in the ends accounting for up to 11% of the sequenced

base pairs. For the Roche 454 technology, overrepresentation

of amplicon ends versus internal bases is substantially less,

with the ends composing only 5% of the total sequenced

bases; this is likely due to library preparation process differ-

ences between Roche 454 and the short-read length plat-

forms. The overrepresentation of amplicon end sequences is

not only wasteful for the sequencing yield but also decreases

the expected average coverage depth across the targeted

intervals. Therefore, to accurately assess the consequences of

sequence coverage on data quality, we removed the 50 bp at

the ends of the amplicons from subsequent analyses.

Sequence coverage of targeted intervals

For each platform we generated a saturating level of redun-

dant sequence coverage, meaning that increased coverage is

likely to have minimal, if any, effect on data quality. For the

four samples the average sequence coverage depth across the

analyzed base pairs is 43×, 188×, and 841× for Roche 454,

Illumina GA, and ABI SOLiD, respectively (Supplemental

Table 2 in Additional data file 1). For all three NGS technolo-

gies there is greater than a hundred-fold variation in the per-

base sequence coverage depth (Figure 2). We performed sev-

eral analyses to determine if the sample preparation method

and/or a specific class of sequence elements were responsible

for the observed variability (Additional data file 2). We first

tested whether the large variability resulted from pooling of

the amplicons. For 90% of the amplicons the fold difference

in average coverage of unique sequences is less than 2.46,

2.72, and 2.99 on the Roche 454, Illumina GA and ABI SOLiD

platforms, respectively (Supplemental Table 3 in Additional

data file 1), showing that the error in equimolar pooling or

amplicon specific bias (sequence, length) explains only a

small fraction of the observed coverage variability. Next we

examined how the sequence coverage differs within the indi-

vidual amplicons. For Roche 454, Illumina GA, and ABI

SOLiD the average coefficient of variance was 0.33, 0.9, and

0.73, respectively, for all base pairs, and 0.35, 0.84 and 0.76,

respectively, when restricted to unique non-repetitive

sequence, defined here as not present in the RepBase data-

base [16]. These results indicate that unique sequences

present at equimolar amounts in the library generation step

end up being covered at vastly different read depths.

It is important to consider how well the NGS technologies are

able to generate sequence reads containing repetitive ele-

ments as these sequences comprise approximately 45% of the

human genome and may potentially impact genome function.

Compared to unique sequences, the Roche 454 technology

has a 1.25-fold overrepresentation of LINE elements, Illu-

mina GA has greater than 2-fold higher coverage of SINEs,

Alus and simple repeats, while for ABI SOLiD all repetitive

剩余12页未读，继续阅读

zhenghui1988

粉丝: 0

二代测序技术评估：针对人群靶向测序研究

"三代基因组测序技术发展简介与原理概述

NGSRepeatFinder：下一代测序数据的创新重复序列检测算法

Python库bbcu.ngs-snakemake-1.0.3安装指南

Algorithms for Next generation Sequencing

Computational Methods for Next Generation Sequencing Data Analysis

A novel genotyping algorithm for SNP detection using next generation sequencing data

Comparative analysis of algorithms for next-generation sequencing read alignment

Hiding Secret Messages in Living Cells in the Age of Next-Generation Sequencing

Single-sample SNP Detection By Empirical Bayesian Method Using Next Generation Sequencing Data

Algorithms for Next-Generation Sequencing Data epub

最新资源