RNA-seq: impact of RNA degradation on transcript quantification.
RNA-seq: impact of RNA degradation on transcript quantification.
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DOI：
10.1186/1741-7007-12-42
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发表时间：
2014-05-30
期刊：
影响因子：
5.4
通讯作者：
Gilad Y
中科院分区：
文献类型：
--
作者：
Gallego Romero I;Pai AA;Tung J;Gilad Y
在全基因组基因表达谱分析中使用低质量的RNA样品仍然存在争议。目前尚不清楚低质量RNA样品中的转录本降解是否均匀发生，在这种情况下，降解的影响可以通过数据归一化来校正，或者不同的转录本是否以不同的速率降解，从而可能使表达水平的测量产生偏差。这种担忧使得在全基因组表达谱分析中使用低质量RNA样品成为问题。然而，低质量的样本（例如，在实地工作过程中收集的样本）有时是解决具体问题的唯一手段。我们试图量化RNA质量变化对基于RNA-seq数据的基因表达水平估计的影响。为此，我们从组织样本中收集了表达数据，这些组织样本在RNA提取之前被允许衰减不同的时间。我们收集的RNA样本涵盖了RNA完整性编号（RIN）值（通常用于评估RNA质量的指标）的整个范围。我们观察到RNA质量对基因表达水平测量的广泛影响，以及在更多降解样品中文库复杂性的轻微但显著的损失。虽然标准的归一化不能解释退化的影响，但我们发现，通过使用线性模型框架明确控制RIN的影响，我们可以纠正大多数这些影响。我们得出结论，在RIN和感兴趣的效应不相关的情况下，这种方法可以帮助从降解的RNA样品中恢复有生物学意义的信号。
The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be corrected via data normalization, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples (for example, samples collected in the course of fieldwork) are at times the sole means of addressing specific questions. We sought to quantify the impact of variation in RNA quality on estimates of gene expression levels based on RNA-seq data. To do so, we collected expression data from tissue samples that were allowed to decay for varying amounts of time prior to RNA extraction. The RNA samples we collected spanned the entire range of RNA Integrity Number (RIN) values (a metric commonly used to assess RNA quality). We observed widespread effects of RNA quality on measurements of gene expression levels, as well as a slight but significant loss of library complexity in more degraded samples. While standard normalizations failed to account for the effects of degradation, we found that by explicitly controlling for the effects of RIN using a linear model framework we can correct for the majority of these effects. We conclude that in instances in which RIN and the effect of interest are not associated, this approach can help recover biologically meaningful signals in data from degraded RNA samples.
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DOI：
10.3393/jksc.2010.26.5.316
发表时间：
2010-10
期刊：
Journal of the Korean Society of Coloproctology
影响因子：
--
作者：
Hong SH;Baek HA;Jang KY;Chung MJ;Moon WS;Kang MJ;Lee DG;Park HS
通讯作者：
Park HS
影响因子：
14.9
作者：
Imbeaud S;Graudens E;Boulanger V;Barlet X;Zaborski P;Eveno E;Mueller O;Schroeder A;Auffray C
通讯作者：
Auffray C
影响因子：
2.1
作者：
Heinrich, Marielle;Matt, Katja;Schmidt, Ulrike
通讯作者：
Schmidt, Ulrike
影响因子：
12.3
作者：
Gentleman RC;Carey VJ;Bates DM;Bolstad B;Dettling M;Dudoit S;Ellis B;Gautier L;Ge Y;Gentry J;Hornik K;Hothorn T;Huber W;Iacus S;Irizarry R;Leisch F;Li C;Maechler M;Rossini AJ;Sawitzki G;Smith C;Smyth G;Tierney L;Yang JY;Zhang J
通讯作者：
Zhang J
影响因子：
14.9
作者：
Flicek P;Ahmed I;Amode MR;Barrell D;Beal K;Brent S;Carvalho-Silva D;Clapham P;Coates G;Fairley S;Fitzgerald S;Gil L;García-Girón C;Gordon L;Hourlier T;Hunt S;Juettemann T;Kähäri AK;Keenan S;Komorowska M;Kulesha E;Longden I;Maurel T;McLaren WM;Muffato M;Nag R;Overduin B;Pignatelli M;Pritchard B;Pritchard E;Riat HS;Ritchie GR;Ruffier M;Schuster M;Sheppard D;Sobral D;Taylor K;Thormann A;Trevanion S;White S;Wilder SP;Aken BL;Birney E;Cunningham F;Dunham I;Harrow J;Herrero J;Hubbard TJ;Johnson N;Kinsella R;Parker A;Spudich G;Yates A;Zadissa A;Searle SM
通讯作者：
Searle SM