Evaluating methods for isolating total RNA and predicting the success of sequencing phylogenetically diverse plant transcriptomes.
Evaluating methods for isolating total RNA and predicting the success of sequencing phylogenetically diverse plant transcriptomes.
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DOI：
10.1371/journal.pone.0050226
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Wong GK
中科院分区：
文献类型：
--
作者：
Johnson MT;Carpenter EJ;Tian Z;Bruskiewich R;Burris JN;Carrigan CT;Chase MW;Clarke ND;Covshoff S;Depamphilis CW;Edger PP;Goh F;Graham S;Greiner S;Hibberd JM;Jordon-Thaden I;Kutchan TM;Leebens-Mack J;Melkonian M;Miles N;Myburg H;Patterson J;Pires JC;Ralph P;Rolf M;Sage RF;Soltis D;Soltis P;Stevenson D;Stewart CN Jr;Surek B;Thomsen CJ;Villarreal JC;Wu X;Zhang Y;Deyholos MK;Wong GK
下一代测序在转录组的表征和定量中起着核心作用。尽管许多指标都声称量化RNA的质量，但尚未对测序成功的主要决定因素进行大规模的经验评估。我们使用现有和新开发的方法相结合，从324科695种植物的1115个样本中分离出总RNA，这代表了从绿色藻类到开花植物（包括许多具有重要经济意义的植物）超过9亿年的系统发育多样性。然后，我们在Illumina GAIIx和HiSeq平台上对其中的629个样本进行了测序，并进行了大量的比较分析，以确定RNA质量的预测因子和样本中表达的推定基因（支架）的多样性。组织类型（例如，叶与花）在RNA质量、测序深度和支架数量上不同。组织年龄也影响RNA质量，但不影响支架≥1000 bp的数量。总体而言，支架数量的36%的变化可以通过RNA完整性（RIN评分）、RNA纯度（OD 260/230）、测序平台（GAIIx vs HiSeq）和用于测序的总RNA的量的度量来解释。然而，我们的研究结果表明，最常用的RNA质量指标（例如，RIN）是支架数量的弱预测因子，因为Illumina测序对RNA质量的变化是稳健的。这些结果提供了新的见解的方法，是最重要的分离高质量的RNA测序和组装植物转录组。这里提供的方法和建议可以提高效率，降低单个实验室和基因组中心的RNA测序成本。
Next-generation sequencing plays a central role in the characterization and quantification of transcriptomes. Although numerous metrics are purported to quantify the quality of RNA, there have been no large-scale empirical evaluations of the major determinants of sequencing success. We used a combination of existing and newly developed methods to isolate total RNA from 1115 samples from 695 plant species in 324 families, which represents >900 million years of phylogenetic diversity from green algae through flowering plants, including many plants of economic importance. We then sequenced 629 of these samples on Illumina GAIIx and HiSeq platforms and performed a large comparative analysis to identify predictors of RNA quality and the diversity of putative genes (scaffolds) expressed within samples. Tissue types (e.g., leaf vs. flower) varied in RNA quality, sequencing depth and the number of scaffolds. Tissue age also influenced RNA quality but not the number of scaffolds ≥1000 bp. Overall, 36% of the variation in the number of scaffolds was explained by metrics of RNA integrity (RIN score), RNA purity (OD 260/230), sequencing platform (GAIIx vs HiSeq) and the amount of total RNA used for sequencing. However, our results show that the most commonly used measures of RNA quality (e.g., RIN) are weak predictors of the number of scaffolds because Illumina sequencing is robust to variation in RNA quality. These results provide novel insight into the methods that are most important in isolating high quality RNA for sequencing and assembling plant transcriptomes. The methods and recommendations provided here could increase the efficiency and decrease the cost of RNA sequencing for individual labs and genome centers.
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