Reverse Transcription Errors and RNA-DNA Differences at Short Tandem Repeats.
Reverse Transcription Errors and RNA-DNA Differences at Short Tandem Repeats.
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DOI：
10.1093/molbev/msw139
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发表时间：
2016-10
影响因子：
10.7
通讯作者：
Makova KD
中科院分区：
文献类型：
--
作者：
Fungtammasan A;Tomaszkiewicz M;Campos-Sánchez R;Eckert KA;DeGiorgio M;Makova KD
转录本变异对健康和疾病的有机体功能具有重要影响。大多数转录组研究侧重于评估基因表达水平和亚型表征的变异。转录本序列水平的变异是由 RNA 编辑和转录错误引起的，并导致非遗传编码的转录本变异或 RNA-DNA 差异 (RDD)。这种变异尚未得到充分研究，部分原因是逆转录（RT）和测序错误掩盖了其检测。仅评估了转录间碱基替换差异。在这里，我们研究了短串联重复序列 (STR) 的转录序列变异。我们开发了第一个最大似然估计器 (MLE) 来推断 RT 错误和 RDD 率，并将下一代测序错误率考虑在内。使用 MLE，我们在灵长类动物中进行的大规模 DNA 和 RNA 复制测序实验中凭经验评估了 STR 的 RT 错误和 RDD 率。 RT 错误率随着 STR 长度呈指数增加，并且偏向于扩展。 RDD 率比 RT 错误率低大约 1 个数量级。使用 MLE 从灵长类数据集估计的 RT 错误率与使用独立方法（条形码 RNA 测序）从秀丽隐杆线虫数据集估计的 RT 错误率一致。我们的结果对医学基因组学具有重要意义，因为 STR 等位基因变异与超过 40 种疾病相关。 STR 非等位基因转录变异也可能导致疾病表型。这里提出的 MLE 和经验率可用于评估 RDD 引起的疾病相关转录本的概率。
Transcript variation has important implications for organismal function in health and disease. Most transcriptome studies focus on assessing variation in gene expression levels and isoform representation. Variation at the level of transcript sequence is caused by RNA editing and transcription errors, and leads to nongenetically encoded transcript variants, or RNA–DNA differences (RDDs). Such variation has been understudied, in part because its detection is obscured by reverse transcription (RT) and sequencing errors. It has only been evaluated for intertranscript base substitution differences. Here, we investigated transcript sequence variation for short tandem repeats (STRs). We developed the first maximum-likelihood estimator (MLE) to infer RT error and RDD rates, taking next generation sequencing error rates into account. Using the MLE, we empirically evaluated RT error and RDD rates for STRs in a large-scale DNA and RNA replicated sequencing experiment conducted in a primate species. The RT error rates increased exponentially with STR length and were biased toward expansions. The RDD rates were approximately 1 order of magnitude lower than the RT error rates. The RT error rates estimated with the MLE from a primate data set were concordant with those estimated with an independent method, barcoded RNA sequencing, from a Caenorhabditis elegans data set. Our results have important implications for medical genomics, as STR allelic variation is associated with >40 diseases. STR nonallelic transcript variation can also contribute to disease phenotype. The MLE and empirical rates presented here can be used to evaluate the probability of disease-associated transcripts arising due to RDD.
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4.1
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